Plants have evolved two opposing strategies in response to competition for light: shade tolerance and shade avoidance. To detect the presence of neighboring vegetation, shade-avoiding plants have evolved the ability to perceive and integrate multiple signals. Among them, changes in light quality and quantity are central to elicit and regulate the shade avoidance response. Here, we describe recent advances in the understanding of photoperception and downstream signaling mechanisms underlying the shade avoidance response, focusing on Arabidopsis because most of our knowledge derives from studies conducted in this model plant. Shade avoidance is an adaptive response, resulting in phenotypes with high relative fitness in natural dense communities. However, it contributes to reduction in crop plant productivity, and the design of new strategies aimed at attenuating shade avoidance in a stage- and/or organ- specific manner in high-density crop plantings is a major challenge for the future. For this reason, in this review, we also report on recent advances in the molecular description of the shade avoidance response in crops, such as maize and tomato, and discuss similarity and differences with Arabidopsis.

We report on the study of energy-harvesting performance in medium-size (400 cm²) glass-based semitransparent solar concentrators employing edge-mounted photovoltaic modules. Systems using several different types of glazing system architecture and containing embedded diffractive structures are prepared and characterized. The technological approaches to the rapid manufacture of large-area diffractive elements suitable for use in solar window-type concentrators are described. These elements enable the internal deflection and partial trapping of light inside glass-based concentrator windows. We focus on uncovering the potential of pattern-transfer polymer-based soft lithography for enabling both the improved photon collection probability at solar cell surfaces, and the up-scaling of semitransparent solar window dimensions. Results of photovoltaic characterization of several solar concentrators employing different internal glazing-system structure and diffractive elements produced using different technologies are reported and discussed.

Non-canonical NF-kB signalling plays important roles in development and function of the immune system but also is deregulated in a number of inflammatory diseases. Although, NF-kB and HIF crosstalk has been documented, this has only been described following canonical NF-kB stimulation, involving RelA/p50 and the HIF-1 dimer. Here we report that the non-canonical inducer TNFSF14/LIGHT leads to HIF induction and activation in cancer cells. We demonstrate that only HIF-2a is induced at the transcriptional level following non-canonical NF-kB activation, via a mechanism dependent on the p52 subunit. Furthermore, we demonstrate that p52 can bind to the HIF-2a gene in cells. These results indicate that non-canonical NF-kB can lead to HIF signalling implicating HIF-2a as one of the downstream effectors of this pathway in cells.

Fibrillin (FBN) is a plastid lipid-associated protein found in photosynthetic organisms from cyanobacteria to plants. In this study, 10 CsaFBN genes were identified in genomic DNA sequences of cucumber (Chinese long and Gy14) through database searches using the conserved domain of FBN and the 14 FBN genes of Arabidopsis. Phylogenetic analysis of CsaFBN protein sequences showed that there was no counterpart of Arabidopsis and rice FBN5 in the cucumber genome. FBN5 is essential for growth in Arabidopsis and rice; its absence in cucumber may be because of incomplete genome sequences or that another FBN carries out its functions. Among the 10 CsaFBN genes, CsaFBN1 and CsaFBN9 were the most divergent in terms of nucleotide sequences. Most of the CsaFBN genes were expressed in the leaf, stem, and fruit. CsaFBN4 showed the highest mRNA expression levels in various tissues, followed by CsaFBN6, CsaFBN1, and CsaFBN9. High-light stress combined with low temperature decreased photosynthetic efficiency and highly induced transcript levels of CsaFBN1, CsaFBN6, and CsaFBN11, which decreased after 24 h treatment. Transcript levels of the other seven genes were changed only slightly. This result suggests that CsaFBN1, CsaFBN6, and CsaFBN11 may be involved in photoprotection under high-light conditions at low temperature.

Semiconductor materials have been shown to have better photocatalytic behavior and can be utilized for the photodegradation of organic pollutants. In this work, three-dimensional flower-like SnS₂ were synthesized by a facile hydrothermal method. Core-shell structured SiO₂@α-Fe₂O₃ nanocomposites were then deposited on the top of the SnS₂ flowers. The as-synthesized nanocomposites were characterized by X-ray diffraction (XRD), Raman spectroscopy, field emission scanning electron microscopy (FE-SEM), Brunauer-Emmett-Teller (BET) and photoluminescence spectroscopy (PL). The photocatalytic behavior of the SnS₂-SiO₂@α-Fe₂O₃ nanocomposites was observed by observing the degradation of methylene blue (MB). The results show an effective enhancement of photocatalytic activity for the degradation of MB especially for the 15 wt. % SiO₂@α-Fe₂O₃ nanocomposites on SnS₂ flowers.

We have experimentally analyzed multi-azimuth degradation mechanisms that govern failures of commercially-available high-power (1 Watt) phosphor-coated white (hppc-W) light-emitting diodes (LEDs) covered with peanut-shaped lens under three current-stress aging (CSA) conditions. Comprehensive analyses focus on photometric, chromatic, electrical, thermal, and packaging characteristics. At the packaging level, (a) the decrease of the phosphor-conversion efficiency, (b) the yellow-browning of the optical lens, and (c) the darkening of the silver-coated reflective layer deposited with extraneous chemical elements (e.g., C, O, Si, Mg, and Cu, respectively) contribute collectively to the integral degradation of the optical power. By contrast, Ohmic contacts, thermal properties, and angles of maximum intensity remain unchanged after 3840 h aging in three cases. Particularly at the chip level, the formation of point defects increases the number of non-radiative recombination centers, and thus decreases the optical power during aging stages. Nevertheless, in view of the change of the ideality factor, the dopant activation and the annealing effect facilitate the increase of the optical power in two specific aging stages (192 h∼384 h and 768 h∼1536 h), respectively. This work offers a systematic guidance for the development of reliable LED-based light sources in general-lighting areas.

Outdoor lighting is becoming increasingly widespread, and residents are suffering from serious light pollution as a result. Residents’ awareness of their rights to protection has gradually increased. However, due to the sometimes-inaccessible nature of residential vertical light incidence intensity data and the high cost of obtaining specific measurements, there is no appropriate hierarchic compensation for residents suffering from different degrees of light pollution. It is therefore important to measure light pollution levels and their damage at the neighborhood scale to provide residents with basic materials for proper protection and to create more politically suitable solutions. This article presents a light pollution assessment method that is easy to perform, is low-cost, and has a short data-processing cycle. This method can be used to monitor residential zone light pollution in other cities. We chose three open areas to test the spatial variation pattern of light intensity. The results are in accordance with spatial interpolation patterns and can be fit, with high precision, using the IDW method. This approach can also be used in 3 dimensions to quantitatively evaluate the distribution of light intensity distribution. We use a mixed-use zone in Beijing known as The Place as our case study area. The vertical illumination at the windows of residential buildings ranges from 2 lux to 23 lux; the illumination in some areas is far higher than the value recommended by CIE. Such severe light pollution can seriously interfere with people's daily lives and has a serious influence on their rest and health. The results of this survey will serve as an important database to assess whether the planning of night-time lighting is scientific and whether it provides residents with a basis for the protection of their rights.

This study introduces an advanced dual-mode composite attitude control framework for reusable launch vehicles (RLVs), underpinned by an enhanced particle swarm optimization (PSO) algorithm. This innovative strategy is tailored to meet the stringent demands for precision and robust anti-interference capabilities across the entire flight envelope of RLVs. The research commences with the formulation of a comprehensive attitude dynamics model and diverse heterogeneous actuator representations, meticulously crafted to reflect the distinct phases of RLV flight. Building upon this foundation, a synergistic control paradigm is engineered, integrating PID and fuzzy PID controllers, complemented by a refined fitness evaluation function. The crux of the study is the application of an upgraded PSO algorithm to fine-tune the controllers' weighting coefficients, culminating in an optimized dual-mode composite attitude control system. A series of comparative simulation analyses are meticulously executed to appraise the system's responsiveness, stability, precision, and resilience to interference. The findings unequivocally substantiate the superior performance of the proposed control system, affirming its substantial contribution to the advancement of RLV attitude control.

This work presents a Fault-Tolerant Model Predictive Control (FTMPC) algorithm applied to a simulation model for sewer networks. The control system will aim to prevent contaminated water from escaping the network, especially during periods of heavy rainfall, that can cause combined sewer overflows (CSO), while maintaining the flow of water towards the wastewater treatment plant (WWTP) as close as possible to its nominal value. The main purpose of the work is to preserve the operation of the predictive controller as much as possible, in accordance with its operational objectives, when there may be anomalies affecting the elements of the control system, mainly sensors and actuators. Comparing the results obtained considering various types of faults, with situations of normal controlled operation and with the behavior of the sewer network when no control is applied, will allow some conclusions to be drawn at the end.

This paper addresses the input coupling problem for the shape memory alloy (SMA) actuated parallel platform with completely unknown nonlinear dynamics. The problem means that in a parallel platform with multiple SMA actuators acting together, the displacement of one of the actuators will simultaneously affect the remaining actuators to change. Due to the coupling problem and nonlinear characteristics of the SMA actuators, it is not easy to control the platform to achieve bi-directional swing with completely unknown nonlinear dynamics. Therefore, a model-free adaptive sliding mode control method is proposed to improve the control accuracy of the complex motion of the platform, avoiding the complex modeling process of the SMA actuated parallel platform. Based on the model-free adaptive control (MFAC) theory, a multiple input and multiple output (MIMO) dynamic linearized mathematical model of the parallel platform is established using the online input and output data of the system. Then, a sliding mode controller is designed based on the dynamic model. A rigorous theoretical analysis proves that the proposed model-free adaptive sliding mode controller is able to stably control the SMA actuated parallel platform, and its tracking error is uniformly ultimately bounded (UUB). Finally, experiments are conducted on the established SMA actuated parallel platform. The results show that the proposed model-free controller is feasible and effective, and can control the system well to achieve the complex motion of bi-directional swing.

We consider a constrained optimal control problem and an extension of it, in which the set of strict-sense trajectories is enlarged. Extension is a common procedure in optimal control, used to derive necessary and sufficient optimality conditions for the original problem from the extended one, which usually admits a minimizer and has a more regular structure. However, this procedure fails if the two problems have different infima. It is therefore relevant to identify such situations. Following on from earlier work by Warga but adopting perturbation techniques developed in non-smooth analysis, we investigate the relation between the occurrence of an infimum gap and abnormality of necessary conditions. For a notion of local minimizer based on control distance and an extension including the impulsive one, we prove that (i) a local extended minimizer which is not a local minimizer of the original problem and (ii) a local strict-sense minimizer which is not a local minimizer of the extended problem, both satisfy the extended maximum principle in abnormal form. The main novelty is result (ii), as until now it had only been shown that a strict-sense minimizer which is not an extended minimizer is abnormal for an `averaged version’ of the maximum principle.

In the last decade, robotic-mediated rehabilitation has emerged as a potential solution to improve repetitive task training. Each device in this field has a unique development history shaped by engineers’ expertise in specific programming languages or platforms. In this work we adopt an approach that tries to abstract from the final implementation with the aim to make control logic more shareable and understandable. The authors will present the outcomes of the application of a Rapid Control Prototyping strategy to an upper-limb robotic exoskeleton. A model-based design approach implemented on a real-time target machine is presented. This modern design approach was explored with several control strategies and was used to test the exoskeleton’s performances. The proposed method highlights how it is possible to develop the entire control architecture in a single programming environment.

The increased cultivation of high THC-containing Cannabis sativa L. (cannabis), particularly in greenhouses, has resulted in a greater incidence of diseases and molds that can negatively affect the growth and quality of the crop. Among them, the most important diseases are root rots (Fusarium and Pythium spp.), Botrytis bud rot (Botrytis cinerea), powdery mildew (Golovinomyces ambrosiae), cannabis stunt disease (caused by Hop latent viroid), and a range of microbes that reduce post-harvest quality. An integrated management approach to reduce the impact of these diseases/microbes requires combining different approaches that target the reproduction, spread and survival of the associated pathogens, many of which can occur on the same plant simultaneously. These approaches will be discussed in the context of developing an integrated plan to manage the important pathogens of greenhouse-grown cannabis at different stages of plant development. These stages include maintenance of stock plants, propagation through cuttings, vegetative growth of plants, and flowering. The cultivation of cannabis genotypes with tolerance or resistance to various pathogens is a very important approach, followed by the maintenance of pathogen-free stock plants. When combined with cultural approaches (sanitation, management of irrigation, and monitoring for diseases) and environmental approaches (greenhouse climate modification), a significant reduction in pathogen development and spread can be achieved. The use of preventive applications of microbial biological control agents and reduced risk biorational products can also reduce disease development at all stages of production in jurisdictions where they are registered for use. The combined use of promising strategies for integrated disease management on cannabis plants during greenhouse production will be reviewed. Future areas for research are identified.

Artificial intelligence (AI) has found extensive applications in the sustainability domain. The municipal solid waste incineration (MSWI) process can achieve waste-to-energy (WTE) goals through the assistance of automation and information technologies. In theory, AI can facilitate the intelligent operation of the MSWI process, simultaneously achieving low pollution emissions and high production efficiency. This study provides an overview of AI applications in the MSWI process. Addressing fundamental challenges, the optimal control of the MSWI process is categorized into four aspects: modeling, control, optimization, and maintenance. Subsequently, this study conducts a detailed analysis and discussion of AI applications in each of these technological domains. In conclusion, this paper outlines the future research directions and provides an outlook on the fundamental issues pertaining to AI applications in the optimal control of the MSWI process.

To mitigate the interference of waves on offshore operation vessels, heave compensation systems find widespread application. The performance of heave compensation systems significantly influences the efficiency and safety of maritime operations. This paper establishes a mathematical model for winch-based active heave compensation system. It introduces a three-loop active disturbance rejection control (ADRC) strategy encompassing piston position control, winch speed control, and load displacement control, enabling real-time estimation and compensation of system disturbances, thereby enhancing the performance of the heave compensation system. To assess the effectiveness of this control strategy, the study employs Matlab/Simulink and AME Sim to construct a co-simulation model and conducts a comparative analysis with traditional PID control systems. The research findings indicate that the three-loop ADRC position control strategy consistently delivers superior compensation performance across various operational scenarios.

A novel reinforcement learning deep deterministic policy gradient agent-based sliding mode control (DDPG-SMC) approach is proposed to suppress the chattering phenomenon in the attitude control for quadrotors, in the presence of external disturbances. First, the attitude dynamics model of the studied quadrotor is derived and the attitude control problem is described by formulas. Second, a sliding mode controller including its sliding mode surface and reaching law is selected for the nonlinear dynamic system, and the stability of the designed SMC system is supported by Lyapunov stability theorem. Third, a reinforcement learning (RL) agent based on deep deterministic policy gradient (DDPG) is trained to adjust the switching control gain adaptively. During the training process, the input signals of agent are the actual and desired attitude angles, and the output action is the time-varying control gain. Finally, the above trained agent is applied to the SMC as a parameter regulator, to implement the adaptive adjustment of the switching control gain related to reaching law, and the simulation results verify the robustness and effectiveness of the proposed DDPG-SMC method.

This paper proposes the application of force-projecting bilateral control to a master-follower teleoperation system with a pneumatic manipulator on the follower side, and evaluates its effectiveness. The proposed method directly projects the operating force on the master side to the driving force on the follower side, eliminating the need for both position control and external force detection on the follower side, thereby solving the problem of low rigidity and response delay of pneumatic manipulators and providing highly stable sensor-less force presentation against variable environments. In this study, dynamic response analyses of a 1-DOF master-follower system were performed by numerical simulation using a linear system model, followed by experimental verification by implementing an actual system with an external force estimator. The results showed that the proposed force-projecting bilateral control has significantly higher positioning rigidity and better force control stability than the conventional force-reflecting bilateral control. A theoretical consideration was also given using equivalent transformation of force transfer functions to provide evidence for the high stability.

With the development of artificial intelligence technology, manipulators, as an important part of the work of intelligent robots, can replace humans to perform various complex tasks. In recent years, there have been many studies on the remote control of manipulators using various control technologies. Starting from the manufacturing materials of flexible sensors used for manipulators, this paper introduces the base materials, sensing materials, and flexible electrode materials of flexible sensors, respectively, and summarizes the performance of flexible sensors made based on the characteristics of different materials. The basic principles of dipping and coating, lithography, inkjet printing, screen printing, 3D printing and so on are introduced from the perspective of flexible sensor manufacturing process. Some different functions of sensors achieved by different structural designs, such as: tensile cracking, microchannels, etc. are also introduced. Then, from the perspective of recognition accuracy of the manipulator, two kinds of control methods based on flexible sensor by data glove control and surface EMG control are classified and introduced, and the problems existing in three aspects of flexible sensor material preparation, manufacturing process and control series design are summarized. Finally, the possible future research directions in this field are suggested.

This paper presents an analysis of the sensitivity of controlling an autonomous surface object among a group of encountered objects to the inaccuracy of state control process data. For this purpose, a safe and optimal model of the control process was defined. An algorithm for determining the optimal and safe trajectory of an object, based on the multi-object game model, was developed; for comparative analysis, an algorithm for calculating only the optimal trajectory, not taking into account the maneuverability of other objects, was additionally developed. First, simulation-based studies of the algorithms enabled a comparative analysis of a number of different acceptable strategies for optimally shifting the trajectory of maneuvering objects from a single initial direction. Thereafter, the main goal of this paper was implemented: an analysis of the sensitivity characteristics of safe control, assessed with the risk of collision, both on the inaccuracy of navigation data and on the number of possible control strategies. Finally, final conclusions and a plan for further research on the subject of the paper were formulated.

The reactive nature of traditional frequency stability methods can lead to delayed corrective actions and unnecessary loss-of-load. This work presents a distributed model predictive control method for proactive power system frequency stability. Dynamic state estimation model is derived through a particle filter. By being able to estimate the future state of frequency, corrective actions can be taken before the system reaches a critical condition. Proactive approach makes it possible to optimize the response to a disturbance, which results in a decrease of the amount of compensation utilized. The method is tested via Matlab simulations based on Kundur's Two-Area System, and the IEEE 14-Bus system. Performance metrics are provided and evaluated against other contemporary solutions found in literature. Easy-to-derive model, without hard-to-design parameters, indicate potential towards real-life applications.

Chaotic systems are systems whose results are sensitive to the initial conditions. Chaotic systems generally have nonlinearities that can be difficult to model. One example of a chaotic system with nonlinearities is the Lorenz system. The Lorenz system can be used to model weather, wind disturbances, and electronic circuit design, among other applications. In this manuscript, the Lorenz system is modeled and various control methods are applied in an effort to dictate the system’s state and rate trajectories. The combination of the linear feedback and nonlinear feedforward controllers can show over an 80% improvement in state trajectory errors when compared to the baseline run. However, the improved state trajectory performance comes at a cost of as much as 1800% error in the rate trajectories.

For a decade, the studies of dynamic control for unmanned aerial vehicles took a large interest, where drones as a useful technology in different areas were always suffering from several issues like instability-high energy consumption of batteries - inaccuracy of tracking targets. Different approaches are proposed for dealing with the non-linearity issues which present the most important features of this system. This paper describes our focus on the most common control strategies, known as model predictive control MPC, by developing a model based on the sensors embedded in our Tello quadrotor used for indoor purposes. The original controller of Tello quadrotor is supposed to be a slave, where the designed model predictive controller is created in MATLAB and imported to another embedded system, considered as a master; the objective of this model is to track the reference trajectory, almost keeping the stability of the system and ensure the low energy consumption. In the first part, a profound description of the modelling process of a dynamic model for drones is presented, explaining the design of MPC controller with both linear and non-linear strategies built in MATLAB. In the final part, simulation and results are discussed regarding its behaviour and performance, highlighting the MPC model's important role on drones' energy consumption profile.

Across the global construction industry, fatalities continue to occur from high-risk activities where the risk controls have been defined, however were unreliable. In the mining industry, Critical Control Risk Management has provided positive results in reducing major accidents, which raises the question, could the Critical Control approach reduce the fatality rate in the construction industry? This study analysed 10 years of serious and fatal incident investigation reports from four international construction companies to i) assess the reliability of their Critical Controls (CCs) and ii) assess the factors which affect the reliability of CCs. The results show the reliability of CCs, measured by implementation and effectiveness, averaged just 42%. Human performance factors including risk identification, decision-making and competency together with supervision, job planning, communication organisational factors were identified as affecting the reliability of CCs. The study used bow-tie diagrams with real event data to find the actual CC effectiveness. This gave actionable findings directly related to individual CCs enabling the participating organization to focus resources on improving specific verification processes. The results confirm the applicability of CCs for the Major Accident Event hazards analyzed and highlights further review is required of the factors which need to be considered when implementing a CC program. This paper details our methodology and results, to assist others apply CCs as a risk management tool.

The paper presents the possibility of using KINECT v2 module to control an industrial robot by means of gestures and voice commands. It describes elements of creating software for off-line and on-line robot control. The application for KINECT module was developed in C# language in Visual Studio environment, while the industrial robot control program was developed in RAPID language in RobotStudio environment. The development of a two-threaded application in RAPID language allowed to separate two independent tasks for the IRB120 robot. The main task of the robot is performed in thread no. 1 (responsible for movement). Simultaneously working thread no. 2 ensures continuous communication with the KINECT system and provides information about the gesture and voice commands in real time without any interference in thread no. 1. The applied solution allows the robot to work in industrial conditions without negative impact of communication task on the time of robot’s work cycles. Thanks to the development of a digital twin of the real robot station, tests of proper application functioning in off-line mode (without using a real robot) were conducted. Obtained results were verified online (on the real test station). Tests of correctness of gesture recognition were carried out, the robot recognized all programmed gestures. Another test carried out was the recognition and execution of voice commands. A difference in the time of task completion between the actual and virtual station was noticed - the average difference was 0.67 s. The last test carried out was to examine the impact of interference on the recognition of voice commands. With a 10dB difference between the command and noise, the recognition of voice commands was equal to 91.43%. The developed computer programs have a modular structure, which enables easy adaptation to process requirements.

Object of this work is the design and the simulation of a hybrid UAV with VTOL capabilities that has been designed for landing on naval moving platforms. The work is focused on the innovative propulsion layout adopted on the UAV. Authors discuss how adopted low level control strategies can exploit the innovative features of the proposed system assuring a good rejection of transversal wind disturbances. Particular attention is dedicated to low level modelling and control of the system emphasizing how choices regarding low level actuation and control should improve performances and robustness of the system.

Electromagnetic actuation can support many fields of technology, such as robotics or biomedical applications. In this context, fully understanding the system behavior and proposing a low-cost package for feedback control is challenging. Modeling the electromagnetic force is particularly tricky because it is a nonlinear function of the actuated object’s position and coil’s current. Measuring in real time the position of the actuated object with the precision required for accurate motion control is also nontrivial. In this study, we propose a novel, cost-effective electromagnetic set-up to achieve position control via visual feedback. We actuate vertically and under different experimental conditions a 10 mm diameter steel ball hanging on a low-stiffness spring, demonstrating good tracking performance (the position error remains within ±0.5 mm with a negligible phase delay in the best scenarios). The experimental results confirm the feasibility of the proposed set-up, which is characterized by minimum complexity and realized with off-the-shelf and cost-effective components. For these reasons, such a contribution helps to understand and apply electromagnetic actuation even further.

Peripheral and autonomic neuropathy are common disease manifestations in systemic amyloidosis. Neurofilament light chain (NfL), a neuron-specific biomarker, is released into the blood and cerebrospinal fluid after neuronal damage. This systematic review provides an overview on the value of NfL in early detection of neuropathy, central nervous system involvement, monitoring of neuropathy progression, and treatment effect in systemic amyloidosis. A literature search in PubMed, Embase and Web of Science was performed on 14-02-2024 for studies investigating NfL levels in patients with systemic amyloidosis and transthyretin gene variant (TTRv) carriers. Only studies containing original data were included. Included were twelve full-text articles and six abstracts describing 1604 participants: 298 controls and 1306 TTRv carriers or patients with or without polyneuropathy. Patients with polyneuropathy demonstrated higher NfL levels compared to healthy controls and asymptomatic carriers. Disease onset was marked by rising NfL levels. Following initiation of transthyretin gene-silencer treatment, NfL levels decreased and remained stable over an extended period. NfL is not an outcome biomarker, but an early and sensitive disease process biomarker for neuropathy in systemic amyloidosis. Therefore, NfL has potential to be used for early detection of neuropathy, monitoring treatment effect, and monitoring disease progression in patients with systemic amyloidosis.

With the increasing use of automatic transmissions in passenger vehicles, there is a growing need for improved gear shifting control strategies that aim to enhance performance and fuel efficiency. This paper introduces a knowledge-based fuzzy control system designed specifically for automatic transmissions in light vehicles. The proposed system utilizes a fuzzy inference system as the controller, enabling the emulation of the driver’s perceptions during the gear shifting process. Consequently, the input signal consists of variables that are either sensitive to or observable by the driver, while the output represents the selected gear. The paper evaluates three distinct control strategies, each based on different inputs. These inputs include the longitudinal velocity of the vehicle, the angular velocity of the engine, or a combination of both, along with the time-derivative of the throttle valve opening. Through the evaluation, it is observed that the combination of inputs yields significantly improved performance. Therefore, the methodology presented in this paper demonstrates that the combined input approach is more effective for gear shifting control.

This study investigates the fixed-time consensus-based attitude control problem for large telescope on-orbit construction subject to discrete-time communication, unknown tiny disturbance torque, model uncertainty, and actuator saturation under an undirected communication graph. Motivated by the need to save wireless communication resources, the communication scheme was designed to exploit interference, which can save communication resources in proportion to the number of modular unit mirrors. Then, a fixed-time observer with discrete-time communication was proposed, which also handles the unknown channel attenuation problem when exploiting information interference. Moreover, based on the backstepping procedure and the suitably defined adaptive compensation law, the fixed-time attitude consensus control law was proposed to handle unknown tiny disturbance torque, model uncertainty, and actuator saturation. Finally, comparative simulation results were provided to verify the effectiveness of the fixed-time observer and proposed fixed-time control law.

: To improve the efficiency of rhizobial inoculation operations and address the current situation of rhizobial inoculation being labor-intensive, a spraying and control system for variable rate application (VRA) of liquid rhizobia was developed. The system can accurately regulate the spraying rate of liquid rhizobia according to the desired rate of rhizobia by incremental Proportional Integral Derivative (PID) closed-loop control algorithm, making it particularly suitable for precise spraying with small amounts. In the laboratory experiment of precise flow control, variation coefficient of spraying nozzle from 0.10 MP to 0.20 MP pressure were no more than 1.2%. A clear linear relationship was observed between the spraying rate and pressure. The maximum response time was 1.93 seconds, while the average response time was 1.62 seconds when controlling the spraying system for small amounts. Field trial was conducted in Heilongjiang Agricultural Xianghe Farm of China. Average seeds number and 100-seed weight of soybean plant with rhizobia inoculation treatment were better than control group, and average yield of spraying liquid rhizobia agent with full base fertilizer increased by 232.5 kg/hm2, representing a significant 7.4% improvement over the control group. The results of these trails clearly showed the positive effect of the spraying and control system for liquid rhizobial inoculation, which has superior to existing inoculation manners, and provides an important technical support for the widespread adoption of rhizobia technology.

The uncertainty in the secondary path of an Active Noise Control (ANC) headphone affects the waterbed effect and stability of the feedback system. This study focuses on the uncertainty of the secondary path when real users wear headphones, and proposes a new uncertainty constraint based on the measured results of the secondary path transfer function under different wearing conditions of dummy head and limited subjects. This constraint and a cascaded second-order infinite impulse response filter with fixed coefficients are used to formulate a control strategic function, which is optimized by the Improved Grey Wolf Optimizer (IGWO) algorithm to obtain the optimal controller with better noise reduction performance. The proposed method and simulation model are validated based on the experimental test results. The results demonstrate that the safety factor and waterbed suppressing factor contained in the proposed uncertainty constraint ensures more stable noise reduction and effective suppression of the waterbed effect for new subjects without a priori data.

This paper presents a cascade predictive control structure based on the field-oriented control (FOC) in the dq rotor reference frame for the synchronous reluctance machine (SynRM). The constant d-axis current control strategy was used and thus, the electromagnetic torque was directly controlled by the q-axis current. Because the model of the two axes currents from the inner loop is a coupled non-linear multivariable one, to non-interaction linear control the two currents, their decoupling was achieved through feedforward components. Following the decoupling, two independent monovariable linear systems resulted for the two currents dynamics that were controlled using model predictive control (MPC) algorithms, considering their ability to automatically handle the state bounds. The most important bounds for SynRM are the limits imposed on currents and voltages, which in the dq plane correspond to a circular limit. To avoid computational effort, linear limitations were adopted through polygonal approximations, resulting in rectangular regions in the dq plane. For the outer loop that controls the angular speed with a constrained MPC algorithm, as plant was considered the q-axis current closed loop dynamics and the torque linear equation. To evaluate the performances of the proposed cascade predictive control structure, a simulation study using MPC controllers versus PI ones was conducted.

A novel approach to the remote-control system for the compact multi-crystal energy-dispersive spectrometer for x-ray emission spectroscopy (XES) applications has been developed. This new approach is based on asynchronous communication between software components and on reactive design principles. In this paper, we identify the challenges we have faced, our solution to them as well as the implementation and future development prospects. The main motivation of this work was the development of a new holistic communication protocol that can be implemented to control various hardware components.

The purpose of this paper is to find the time optimal control to a target set for semilinear stochastic functional differential equations involving time delays or memories under general conditions on a target set and nonlinear terms even though the equations contain unbounded principal operators. Our research approach is construct a fundamental solution for corresponding linear systems and establish variations of constant formula of solutions for given stochastic equations. The existence result of time optimal controls for one point target set governed by the given semilinear stochastic equation is also established.

Abstract: The article proposes to consider the possibility of connecting the problems of engineering synthesis of frequency control systems for asynchronous electric drives with the basic provisions of the theory of identification of asynchronous electric motors based on the equations of a generalized AC electric machine.The article presents the results of experimental studies of load parrying processes in asynchronous electric drives with vector and scalar controls. These results indicate the absence of fundamental advantages as processes in a drive with vector control. This advantage should have manifested itself in a more efficient formation of the moment and fast transients. It is suggested that the reason for this is in too significant errors, assumptions and simplifications of the equations adopted in the derivation of vector control and which are its theoretical basis. A method is proposed for describing asynchronous electric motors by nonlinear transfer functions, which made it possible to formulate the principle of correction of electric drives and a method for assessing their efficiency.The article shows. that the correction based on the proposed nonlinear transfer functions of the induction motor is much more efficient than the traditional vector control, which was confirmed by detailed experiments and modeling. The results of the most important of which are given in the article. An assumption was made. that the advantage in efficiency is due to a more accurate identification of the dynamics of an asynchronous electric motor with a gear function instead of vector equations.

In this paper, modelling designing and simulation of a simple voltage amplidyne system is done using robust control theory. In order to increase the performance of the voltage amplidyne system with H ∞ optimal control synthesis and H ∞ optimal control synthesis via ∞-iteration controllers are used. The open loop response of the voltage amplidyne system shows that the system can amplify the input 7 times. Comparison of the voltage amplidyne system with H ∞ optimal control synthesis and H ∞ optimal control synthesis via ∞-iteration controllers to track a desired step input have been done. Finally, the comparative simulation results prove the effectiveness of the proposed voltage amplidyne system with H ∞ optimal control synthesis controller in improving the percentage overshoot and the settling time.

This paper studies the integrated design problems of control and guidance with parameter uncertainties, target disturbances, input constraints and actuator faults. Firstly, based on the integrated design idea of the missile guidance and control, the auxiliary variable is used to establish and transform it into a cascade system with input constraints, actuator faults and disturbances of unknown upper bounds. Secondly, the adaptive anti-saturation dynamic surface fault-tolerant controller is designed by using the back-stepping method, adaptive control, auxiliary system and tracking differentiator. By introducing the tracking differentiator and tangent barrier Lyapunov function, the computational explosion problem in the traditional back-stepping method is avoided and the angle of attack can be guaranteed in prospective range, respectively. Finally, the theoretical proof of the designed control strategy is given to ensure that the states of the closed-loop system are bounded. At the same time, the digital simulation of the maneuvering target of different maneuvering forms is carried out, which further illustrate the effectiveness and robustness of the designed control schemes.

Cloud-based CNC is an emerging paradigm of Industry 4.0 where computer numerical control (CNC) functionalities are moved to the cloud and provided to manufacturing machines as a service. Among many benefits, C-CNC allows manufacturing machines to leverage advanced control algorithms running on cloud computers to boost their performance at low cost, without need for major hardware upgrades. However, a fundamental challenge of C-CNC is how to guarantee safety and reliability of machine control given variable Internet quality of service, especially on public Internet networks. We propose a three-tier redundant architecture to address this challenge. We then prototype tier one of the architecture on a 3D printer successfully controlled via C-CNC over public Internet connections, and discuss follow-on research opportunities.

This contribution considers an improved control scheme for three-phase two-stage grid-tied photovoltaic (PV) power system based on integral sliding mode control (ISMC) theory. The proposed control scheme consists of maximum power point tracking (MPPT), DC-Link voltage regulation and grid currents synchronization. A modified voltage-oriented maximum power point tracking (VO-MPPT) method based on ISMC theory is proposed for design of an enhanced MPPT under irradiation changes. Moreover, a novel DC-Link voltage control based on ISMC theory is proposed in order to achieve good regulation of DC-Link voltage over its reference. To inject the generated PV power into the grid with high quality, a voltage oriented control based on space vector modulation (SVM) and ISMC (VOC-ISMC-SVM) has been developed to control the grid currents synchronization. Numerical simulations are performed in Matlab/SimulinkTM environment in order to evaluate the proposed control strategy. In comparison with conventional control scheme, the developed control strategy provides an accurate MPP tracking with less power oscillation as well as a fast and an accurate DC-Link regulation under climatic conditions variations. Moreover, the transfer of the extracted power into the grid is achieved with high quality.

Microalgae are photosynthetic microorganism able to receive light from sunlight and external light sources for their growth. Despite the simplicity of cultivation and their widespread presence, the growth of microalgae is affected by several factors, light intensity being a crucial one as it is linked to external environmental conditions. On the other hand, microalgae cultivation in wastewater with high nitrogen content has become a promising alternative as a low cost nutrients substrate method. However, effluents may contain many compounds, making therefore difficult the assessment of light intensity on cells growth profile and especially on nutrients assimilation rate. The aim of this study was the examination of the effect of intensity of light source on the growth and nutrient uptake rates by a freshwater microalgae, Chlorella sorokiniana in the effluent from an anaerobic digestion plant, with nitrogen content reaching up to 5 g/L. Microalgae were cultivated using three light intensities (1,500, 5,000 and 12,000 lx) in 10% digestate mixtures in water. Samples were collected and analyzed for the presence of microalgae cells, while aqueous phase samples were subjected to the analysis of nitrogen and phosphorous content. Biomass productivity followed the light intensity pattern: the highest the light the highest the cells growth. A similar pattern was observed in the reduction rate of nitrogen and phosphorous concentrations; however, nutrients reduction rate per gram of microalgae were mainly associated to biomass growth rate, indicating that the effect of light intensity was significant for biomass growth, without however changing the main nutrients assimilation pathway. In addition, results indicated that under high light intensity, microalgae might change their metabolism towards formation of lipids against nitrogenous compounds.

The monocular structured light measurement system has low cost, simple algorithms, and a wide measurement range, making it widely applicable in multiple fields. However, in practical applications, the system may be affected by various factors including noise, non-linear intensity, changes in the reflectivity of the object being measured, and the calibration method and accuracy of the system, thereby reducing the measurement accuracy. In order to solve these issues, this paper proposes a new monocular structured light measurement method, mainly comprises the following two points: (a) A denoising algorithm for phase images based on DAE is proposed, which calculates the wrapped phase of the phase-shifted fringes after initial denoising by DAE. Then, a new phase-shifted fringe pattern is generated and input into DAE for iterative denoising, achieving high-performance image denoising and high-precision wrapped phase solution. (b) A new absolute phase height calibration algorithm is proposed, which introduces camera internal and external parameters and uses a two-layer feedforward network to directly establish the relationship between phase and the 3D coordinate system. Without the need for high-precision motion platforms, high-precision phase height calibration is attainable. In general, compared to conventional methods, the experimental results indicate the effectiveness of the proposed method for low-quality phase-shifted fringe 3D reconstruction. In addition, the measurement method described in this article also demonstrates effectiveness in high-dynamic scenes.

Efficient traffic flow management at intersections is vital for optimizing urban transportation networks. This paper presents a comprehensive approach to refining traffic flow by analyzing the capacity of roads and integrating fuzzy logic-based traffic light control systems. We were examining the capacity of roads connecting intersections, considering factors such as road vehicle capacity, vehicle speed, and traffic flow volume, through detailed mathematical modelling and analysis. Control is determined by the maximum capacity of each road segment, providing valuable insights into traffic flow dynamics. Building upon this capacity and flow analysis, the research introduces a novel Intelligent Traffic Light Controller (ITLC) system based on fuzzy logic principles. By incorporating real-time traffic data and lever-aging fuzzy logic algorithms, our ITLC system dynamically adjusts traffic light timings to optimize vehicle flow at two intersections. The paper discusses the de-sign and implementation of the ITLC system, highlighting its adaptive capabilities in response to changing traffic conditions. Simulation results are presented, demonstrating effectiveness of the ITLC system in improving traffic flow and re-ducing congestion at intersections. Furthermore, this research provides an analysis of the mathematical models used to calculate road capacity, offering insights into the underlying principles of traffic flow optimization. Through the simulation, we have validated accuracy and reliability of our controller.

In this work, zinc oxide (ZnO)/ granular activated carbon (GAC) composites at different ZnO concentration (0.25M-ZnO@GAC, 0.5M-ZnO@GAC, and 0.75M-ZnO@GAC) were prepared by an in-situ hydrothermal method and demonstrated synergistic photocatalytic degradation and ad-sorption of Rhodamine B (RhB). The thermal stability, morphological structure, elemental com-position, crystallographic structure, and textural properties of developed catalysts were charac-terized by thermal gravimetric analysis (TGA/DTG), scanning electron microscopy equipped with energy dispersive-x-ray (SEM-EDS), x-ray diffraction (XRD), and Brunauer–Emmett–Teller (BET) analysis. Successful loading of ZnO onto GAC was confirmed by SEM-EDS and XRD analysis. The BET surface areas of GAC, 0.25M-ZnO@GAC, 0.5M-ZnO@GAC, and 0.75M-ZnO@GAC were 474 m2/g, 450 m2/g, 453 m2/g, and 421 m2/g, respectively. The decrease in GAC could be attributed to the successful loading of ZnO on the GAC surface. Notably, 0.5M-ZnO@GAC exhibited the best photocatalytic degradation efficiency of 82% and 97% under UV-A and UV-C light over 120 min, attributed to improved crystallinity and visible light absorption. The photocatalytic degradation parameters revealed that lowering the RhB concentration, raising the catalyst dosage and pH be-yond the point of zero charge (PZC) would favor the RhB degradation. Photocatalytic reusability was demonstrated over 5 cycles. Scavenger tests revealed that the hydroxyl radicals (•OH), su-peroxide radicals (O2−•), and photoinduced hole (h+) radicals play a major role during the RhB degradation process. Based on the TOC results, the RhB mineralization efficiency of 79.1% was achieved by 0.5M-ZnO@GAC. Additionally, GAC exhibited a strong adsorptive performance towards RhB with adsorption capacity and RhB removal of 487.1 mg/g and 99.5% achieved within 90 min equilibrium time. The adsorption characteristics were best described by pseu-do-second-order kinetics, suggesting chemical adsorption. This research offers a new strategy for the development of effective photocatalyst materials with potential for wider wastewater treat-ment applications.

The SBA-15 loaded with methylene blue was successfully prepared by sample adsorption of methylene blue in SBA-15 and is characterized by an XRD, SEM, FTIR, and BET. The photocatalytic activity for methyl orange (MO) degradation was investigated under visible light irradiation under LEDs. Experimental results demonstrate that the SBA-15-MB exhibited higher photocatalytic activity than SBA-15 under visible light irradiation. The degradation efficiency of MO (50 ppm) by SBA-15-MB could reach 80% within 180 min under 25W LED visible light. The photocatalytic activity of SBA-15 could be attributed to the excitation of methylene blue by visible light, the transfer of electrons from methylene blue to SBA-15, and the production of radicals at the surface of SBA-15.

The per capita availability of freshwater resources on a global scale is gradually decreasing due to population growth, rapid urbanization, industrialization, and modern lifestyles. In this situation, wastewater management becomes a major concern. Conventional treatment processes used to treat wastewater discharges are not adequate for the advanced removal of pollutants, especially refractory organic pollutants, which are mainly organic compounds that are not easily biodegradable in the environment. The use of photocatalytic membrane reactors (PMRs) for tertiary wastewater treatment has attracted much interest in recent periods, and various configurations have been investigated. The performance of a PMR using an iron doped titanium photo catalyst and Polysulfone-based polymeric membrane for municipal wastewater treatment was evaluated under natural and simulated solar light. Obtained results proved that solar driven PMRs can remove organic loading (COD) with high efficiencies and may represent a suitable alternative for the tertiary treatment step of municipal wastewater.

In recent years, researches on combining wavelet decomposition and convolutional neural network (CNN) together to classify hyperspectral images (HSI) have emerged, and some effective classification models have been proposed and achieved good classification results. However, there are two problems for most of the proposed models. One is the heavy training parameters and the other is that there is no distinction between the classification effectiveness of low frequency and high frequency features after wavelet decomposition. In this paper, a new light-weighted HSI classification model (LLFWCNN) is proposed, which performs multi-layer wavelet decomposition for HSI after dimensionality reduction, and only arranges the low frequency features in a specific stack mode, then classifies them through a well-designed convolutional neural network. Compared with other classification models, the number of parameters is only 2.5% of that of other models. And only the low frequency features after wavelet decomposition are used, while the high frequency features are abandoned. The results showed that compared with the state-of-the-art classification models, LLFWCNN could obtain the same or even better classification results with fewer network parameters and proved that the low frequency features after wavelet decomposition provide LLFWCNN with more favorable information for HSI classification as well.

Monolayer graphene absorbs 2.3 percent of the incident visible light. This “small” absorption has been used to emphasize the visual transparency of graphene, but it in fact means that multilayer graphene absorbs a sizable fraction of incident light, which causes non-negligible fluorescence. In this paper, we formulate the light emission properties of multilayer graphene composed of tens to hundreds of layers using a transfer matrix method and confirm the method’s validity experimentally. We could quantitatively explain the measured contrasts of multilayer graphene on SiO2/Si substrates and found sizable corrections, which cannot be classified as incoherent light emissions, to the reflectance of visible light. The new component originates from coherent emission caused by absorption at each graphene layer. Multilayer graphene thus functions as a partial coherent light source of various wavelengths, and it may have surface-emitting laser applications.

The agricultural sector faces challenges due to climate change and the growing global population. Alkaline stress could adversely impact plant growth and crop production. This stressor diminishes water quality essential for crop cultivation, consequently impairing plant growth and overall productivity. Gamma-aminobutyric acid (GABA), a non-protein amino acid, may exhibit multifaceted roles in plant responses to adverse environmental conditions. Optimization of crop production in controlled environmental agriculture under artificial light attracted much attention. In the present study, we investigated the effects of different light spectra and GABA concentrations on Lollo Rosso lettuce plants under alkaline stress. Seedlings were placed under different light spectra [red (R), blue (B), white (W), 3R:1B, and 2R:1B:1far-red (FR)] and treated by GABA (0 and 50 µmol). Alkaline conditions were instituted by applying NaHCO3 at a concentration of 40 mM. The experiment incorporated a control treatment without NaHCO3. In general, R light exposure caused the highest growth performance of lettuce plants. GABA augmented biomass production in control and alkaline-treated plants across all light spectra. Additionally, it increased the concentrations of photosynthetic and protective pigments under alkaline conditions. GABA also improved the photosynthetic performance under all light spectra. Non-photochemical quenching and pigmentation were enhanced by exposure to B light, especially in plants treated with GABA. Alkaline stress induced an increase in soluble carbohydrate content in the lettuce leaves. These findings highlight the support of GABA application in facilitating coping plants to alkaline stress.

The rapid and accurate detection of parasites is crucial for timely curative intervention in parasitosis and for epidemiological surveillance. To meet the needs of clinical diagnosis, it is imperative to develop a diagnostic tool based on nucleic acid that combines the sensitivity and specificity of established nucleic acid amplifica-tion tests with the speed, cost-effectiveness, and convenience of isothermal amplification methods. A new nu-cleic acid detection method, utilizing the clustered regularly interspaced short palindromic repeats (CRISPR)-associated (Cas) nuclease, holds promise for point-of-care testing. Specifically, the CRISPR-Cas12a system has demonstrated numerous advantages for detecting parasites, with hopeful outcomes for identify-ing malaria, toxoplasmosis, and other parasitic ailments. This review provides an overview of how CRISPR-Cas12a can be utilized for parasite detection, evaluates its advantages and disadvantages, and sug-gests ways to improve the efficiency and sensitivity of CRISPR-Cas12a-based assays.

Breast cancer is a global health concern, necessitating continuous advancements in diagnostic medical imaging technologies for early detection and improvement of treatment. This paper presents an overview of the past, present and future of breast cancer imaging using light and some results from the current studies. The paper specifically presents the role of Diffuse Optical Tomography (DOT) in breast cancer imaging. Conventional methods, such as X-ray mammography, face limitations. Diffuse Optical Tomography, a non-invasive light-based imaging modality can provide quantitative descriptive and architectural information about breast tissue. The paper discusses the key challenges and recent developments in breast cancer imaging using DOT to overcome some key challenges. This paper aims to contribute to the understanding of the evolving technological landscape in breast cancer imaging using light for improving early detection and patient outcomes.

The LED light source is an important light source for indoor visible light communication. It has the characteristics of a large divergence angle and a high transmission rate. Therefore, using LED as the light source for visible light full-duplex communication can not only satisfy the lighting requirements but also transmit information at high speed. To analyze the factors that affect the optical power of the indoor single-light source visible light communication uplink receiving end, an indoor visible light communication model was established, and mathematical calculation formulas were derived based on the model establishment, and the maximum movable range formula of the retroreflective end under specific conditions was derived; The reliability of the formula was verified with the help of Zemax simulation software. Theoretical analysis and experimental results show that increasing the movement range of the retroreflective end can be achieved by increasing the lens diameter, reducing the focal length, and increasing the link distance.

Legumes are a diverse and important group of plants that play a vital role in agriculture, food security, and environmental sustainability. Rhizobia are symbiotic bacteria that form nitrogen-fixing nodules on legume roots, providing the plant with a valuable source of nitrogen. Phenolic acids are a group of secondary metabolites produced by plants that have a wide range of biological functions, including defense against pests and diseases, tolerance to abiotic stresses, and nutrient uptake. In the context of climate change and the imperative for sustainable agriculture, this study delves into the dynamic responses of legume species to varying light intensities and their intricate interactions with soil microorganisms. We investigated the impact of light intensity and rhizobial inoculation on the biomass, nitrate reductase, acid phosphatase, and production of phenolic acids in the roots of four legume species, Trifolium repens, Vicia sativa, Ornithopus compressus, and Coronilla juncea. Plants were grown under three light intensity regimes (low, medium, and high) and inoculated with either rhizobia or a non-inoculated control. The results highlights that shaded-light-adapted species, T. repens and V. sativa, increased root exudate production when exposed to high light intensity. This response aligns with their mining strategy, effectively allocating resources to optimize nutrient acquisition under varying conditions. In contrast, species hailing from well- illuminated environments, O. compressus and C. juncea, displayed distinct strategies by significantly increasing biomass under high irradiance, capitalizing on the available light and nutrients. The mining strategy of legumes emerged as a central theme, influencing biomass production, nitrogen dynamics, and enzymatic activities. The strong correlations between biomass and total nitrogen accumulation underscore the role of the mining strategy in efficient nutrient acquisition. Inoculated plants, which rely more on biological nitrogen fixation (BNF), exhibited lower δ15N values, indicative of a successful mining strategy to acquire and utilize atmospheric nitrogen. Enzymatic activities and phenolic acids exhibited significant interspecies variations, reflecting the adaptability of legumes to different light conditions. The findings of this study could be used to develop new strategies for improving legume stress tolerance, nutrient uptake capacity, and rhizosphere health.

Super-resolution technology is important not only in bio-related fields but also in nanotechnology, particularly in the semiconductor industry, where fine patterning is required and super-resolution is essential. However, observing microstructures beyond the diffraction limit proposed by Abbe and Rayleigh is considered impossible because of diffraction in traditional optical microscopy ob-servation techniques. However, in recent years, it has been possible to observe microstructures beyond the Rayleigh criterion by analysing the phase distribution of light. This study investigated the physical reasons why phase analysis makes this new analysis technique possible using simula-tions. The results confirmed that the phase component of the zero-order diffracted light reflected from the microstructure and able to pass through the lens system contained the phase information related to the shape of the measured object. Analysis of this information demonstrates the possi-bility of realising super-resolution based on speckle interferometry.

3D printing technology has brought about a paradigm shift in the delivery of clinical care in medicine and dentistry. There are several different 3D printing technologies, which, along with different printable materials with unique biomechanical properties, allows for a wide range of applications for 3D printing in dentistry. The clinical use of 3D printing has created versatile applications which streamline our digital workflow. Technological advancements have also paved the way for the integration of new dental materials in dentistry. This paper provides an overview of the mechanisms of 3D printing, the dental materials relevant to each mechanism and the possible applications of these materials within different areas of dentistry. Understanding the existing spectrum of 3D printing applications in dentistry will serve to further expand its use in the dental field.

Four strains of green microalgae (Scenedesmus acutus, Scenedesmus vacuolatus, Chlorella sorokiniana and Chlamydomonas reinhardtii) were compared for growth and pigment composition under photoautotrophic or heterotrophic conditions. Batch growth experiments were performed in multicultivators with online monitoring of optical density. For photoautotrophic growth, light-limited (CO2-sufficient) growth was analysed under different light intensities during exponential and deceleration growth phases. The specific growth rate, mesured during exponential phase, and the maximal biomass productivity, measured during deceleration phase, were not related to each other when different light intensities and different species were considered. This indicates species-dependent photoacclimation effects during cultivation time, which was confirmed by light-dependent changes in pigment contents and compositions when exponential and deceleration phases were compared. Except for C. reinhardtii, that does not grow on glucose, heterotrophic growth was promoted to similar extents by acetate or by glucose, however these two substrates led to different pigment compositions. Weak light increased pigment contents during heterotrophy in the four species, but was efficient in promoting growth only in S. acutus. C. sorokiniana and S. vacuolatus exhibited the best potential for heterotrophic biomass productivities both on glucose and acetate, with carotenoid (lutein) content being the highest in the former.

: This work introduces the instrument design of the medium energy proton detector (MEPD, detection range: 30keV-5MeV) mounted on the Chinese Fengyun-4B (FY-4B) satellite. Compared with the similar detector on the Fengyun-3E (FY-3E) satellite, the instrument has undergone significant changes due to the different orbital radiation environment and solar lighting conditions. Based on the calculation of radiation model AP8, the geometry factor is reduced to 0.002 cm2sr, while the MEPD on FY-3E satellite is 0.005 cm2sr. Another difference is that sensors in some directions is exposed to direct sunlight for 80 minutes every day on this orbit, depending on the attitude angle of the satellite, which is much worse than that on FY-3E satellite. According to the calculation results of permeability of photons through different materials, a 100 nm thickness nickel film is added in front of sensors in order to eliminate light pollution completely. The experiment on the solar simulator shows that the measure is effective and the detector has no error counts when the solar irradiance coefficient is 1.0. In addition, Geant4 software is applied to simulate particle transportation process under complete machine condition so that to check the contamination of electrons on sensors among all directions after magnetic deflection. Data obtained in orbit shows that the instrument works properly, and the data is in good agreement with the AP8 model. The observations of the MEPD on board the FY-4B satellite can provide important support for the safety of the spacecraft and the theoretical research related to space weather.

Nanoparticles are of great importance for various scientific and technological applications, drug discovery, ecology, molecular biology, etc. Size is a basic characteristic of any particle, and dynamic light scattering is beyond competition when measuring particle size in dispersions ranging from nanometers to micrometers. Unfortunately, this method has a serious problem in processing and interpreting experimental data. Instrument noise and polydispersity of the sample lead to the situation when one initial autocorrelation function corresponds to several different particle size distributions. Sometimes these different solutions of the inverse task can be found by changing parameters in the software. Sometimes the scientist cannot be suspicious of possible other solutions, having one result from the program. In this article I demonstrate the problem on model and experimental data using three known programs: CONTIN, the Malvern Zetasizer and DynaLS. I also present my own free program Autocor, which allows to test our own hypotheses about the modality and shape of the particle size distribution by optimizing the parameters of our own models with a small number of degrees of freedom.

Simultaneous biofortification of vegetable crops with selenium and iodine is necessary in areas where there is a lack of these two elements. The main reason for lack of selenium and iodine in humans is inadequate intake of these two elements from vegetable crops. Biofortification through various agricultural methods including artificial lighting is a pragmatic way of increasing the concentration of these elements in plants. This research was conducted as a three-factor factorial experiment arranged as completely randomized pots replicated thrice in the greenhouse during year 2022. Three levels of sodium selenate fertilizer (S1: 0, S2: 2, S3: 4 mg/l), three levels of potassium iodate (I1: 0, I2: 2, I3: 4 mg/L) and two additional blue light radiation levels (L1: radiation and L2: no blue light radiation) were applied and data was measured at two growth stages namely 40 and 80-days. The results showed that the highest (11.44 g) and the lowest (9.55 g) shoot dry weight values at the 40-day-stage were observed in the supplementary blue light and sunlight (control), respectively. Moreover,, under complementary blue light conditions, the highest and the lowest (5.85 and 3.38 mg/g leaf fresh weight) of leaf chlorophyll value at the 40-day-stage were recorded at sodium selenate 4 and 0 mg/l, respectively. The highest and the lowest (5.24 and 4.76 mg/g) fresh weight of leaf anthocyanin at the 40-day-growth stage were related to supplementary blue light and sunlight treatment (control), respectively. Under the supplementary blue light and 0 mg/l of selenium , the highest and the lowest value of shoot trigonelline (102.56 and 72.14 mg/100 g fresh weight) were obtained at 4 and 2 mg/L of iodine, respectively. Furthermore, in the same treatment, the highest and the lowest of seed trigonelline amounts (0.99 and 0.74 mg/g dry weight) corresponded with 4 and 0 mg/l of iodine, respectively.

Electroactive microorganisms have received a lot of interest in the field of environmental engineering and biotechnology because of their extracellular electron transfer (EET) capability of energy recovery and environmental remediation. However, the low efficiency of EET remains a barrier to its practical implementation. This review presents an introduction to EET, followed by addressing strategies for enhancing EET through different approaches including enhancing EET by mediator materials, external electricity, photo, and magnetism as well as integrated strategies, that is, the combination of multiple means to promote extracellular electron transport and improve the performance of microbial electrochemical systems. Finally, the challenges, perspectives, and new directions for EET enhancement will be discussed.

With the advent of deep learning, significant progress has been made in low-light image enhancement methods. However, deep learning requires enormous paired training data, which is challenging to capture in real-world scenarios.To address this limitation, this paper presents a novel unsupervised low-light image enhancement method, which first introduces the frequency domain features of images in low-light image enhancement tasks. Our work is inspired by imagining a digital image as a spatially varying metaphoric “field of light”, then subjecting the influence of physical processes such as diffraction and coherent detection back onto the original image space via a frequency-domain to spatial-domain transformation (inverse Fourier transform). However, the mathematical model created by this physical process still requires complex manual tuning of the parameters for different scene conditions to achieve the best adjustment. Therefore, we proposed a dual-branch convolution network to estimate pixel-wise and high-order spatial interactions for dynamic range adjustment of the frequency feature of the given low-light image. Guided by the frequency feature from the “field of light” and parameter estimation networks, our method enables dynamic enhancement of low-light images. Extensive experiments have shown that our method performs well compared to state-of-the-art unsupervised, and its performance approximates the level of the state-of-the-art supervised methods qualitatively and quantitatively. At the same time, the light network structure design allows the proposed method to have an extremely fast inference speed(nearly 150 FPS on an NVIDIA 3090 Ti GPU for an image of size 600×400×3 ). Furthermore, the potential benefits of our method to object detection in the dark are discussed.

This paper presents the light scattering matrices of atmospheric aggregated hexagonal ice particles appearing in cirrus clouds. In this work aggregates consist of the same particles with different spatial orientation and number of these particles. Two types of particle shape were studied: (1) hexagonal column; (2) hexagonal plate. For both shapes we study compact and non-compact cases of arrangement of particles in aggregates. As a result, four sets of aggregates were made: (1) compact columns; (2) non-compact columns; (3) compact plates; (4) non-compact plates. Each set consists of eight aggregates with different number of particles from 2 to 9. For practical reason the bullet-rosette and the aggregate of hexagonal columns with different sizes was also calculated. The light scattering matrices were calculated for the case of arbitrary spatial orientation within the geometrical optics approximation for sets of compact and non-compact aggregates and within the physical optics approximation for two additional aggregates. It was found that light scattering matrix elements for aggregates are depend on arrangement of particles they are consisted.

Background and Objectives: Light therapy (LT) is used as an adjunctive treatment for sleep problems. This study evaluates the impact of LT on sleep quality and sleep-related parameters in patients with sleep disorders. Materials and Methods: We performed a pilot randomized, open-label clinical trial. Fourteen patients aged 20–60 years with sleep disorders for more than three months were randomized into the control and LT groups (1:1 ratio). The LT group was instructed to use a device that provides bright LT (6000 K, 380 lux, wavelength 480 nm) for at least 25 minutes before 09:00 am for two weeks. A self-reported questionnaire was used to evaluate circadian preference, mood, and sleep-related parameters. We analyzed serum cortisol levels and clock genes expression. Results: The Epworth Sleepiness Scale (ESS), insomnia severity index, and Pittsburgh Sleep Quality index were significantly improved within the LT group only after the two-week period. When comparing the two groups, only the change in ESS significant was significant (mean difference; control: -0.14 vs LT: -1.43, p=0.021) after adjusting for baseline characteristics. There were no significant differences in serum cortisol or clock genes expression. Conclusions: LT can improve daytime sleepiness in patients with sleep disorders; however, further well-designed studies are warranted to confirm its efficacy.

Introduction: Successful R0 resection is crucial for the survival of patients with primary liver cancer (PLC) or liver metastases. Up to date, surgical resection lacks a sensitive, real-time intraoperative imaging modality to determine R0 resection. Real-time intraoperative visualization with near-infrared light fluorescence (NIRF) using indocyanine green (ICG) may have the potential to meet this demand. This study evaluates the value of ICG visualization in PLC and liver metastases surgery regarding R0 resection rates. Materials and Methods Patients with PLC or liver metastases were included in this prospective cohort study. ICG 10mg was administered intravenously 24 hours before surgery. Real-time intraoperative NIRF visualization was made with the SpectrumTM Fluorescence Imaging Camera System. First, all liver segments were inspected with the fluorescence imaging system and intraoperative ultrasound for identification of the known tumor as well as additional lesions, compared to preoperative MRI. PLC, liver metastases, and additional lesions were then resected according to oncological principles. Of all resected specimens the resection margins were analyzed with the fluorescence imaging system for ICG positive spots right after resection. Histology of additional detected lesions as well as ICG fluorescence compared to histological resection margins were assessed. Results Of the 66 included patients median age was 65.5 years (IQR 58.7 - 73.9), 27 (40.9%) were female and 18 (27.3%) were operated laparoscopically. Additional ICG positive lesions were detected in 23 (35.4%) patients of which nine (29%) were malignant. In patients with no fluorescent signal at the resection margin, R0 rate was 93.9%, R1 rate was 6.1%, and R2 rate was 0% compared to a ICG positive resection margin with a R0 rate of 64.3%, R1 rate of 21.4%, and R2 rate of 14.3% (p=0.005). One and two year overall survival were 95.2% and 88.4%, respectively. Conclusion The here presented study provides significant evidence that ICG NIRF guidance helps to identify R0 resection intraoperatively. This offers a true potential to verify radical resection and improve patients´ outcome. Furthermore, implementation of NIRF guided imaging in liver tumor surgery allows to detect a considerable amount of additional malignant lesions.

Ultra-short laser pulses (1030 nm/230 fs) were used to laser ablate surface of crystalline sapphire. Laser ablated patterns were annealed at high temperature 1500∘C. Surface reconstruction took place removing ablation debris field at the edges of ablated pits in oxygen flow. Partial reconstruction of ripples was also observed.

Bright morning light (BML) entrains the body clock, modulates circadian rhythm, and improves sleep-wake disturbances. However, its impact on the autonomic nervous system (ANS) at night remains unclear. Hence, we investigated the effects of BML exposure on activities of the parasympathetic nervous system (PSNS) and sympathetic nervous system (SNS) at night. This non-randomized controlled pilot study included participants ≥60 years, diagnosed with a type of dementia or cognitive disorder. We excluded participants with pacemakers. The treatment group received 2500 lx BML, whereas the control group received approximately 200 lx of general lighting. We measured the heart rate variability to quantify ANS activity. The treatment group displayed significantly increased high-frequency (HF) power (Roy's largest root=2.44; P<.01) and insignificantly decreased normalized low-frequency (LF%) power. The corresponding low-frequency/high-frequency ratio (LF/HF), insignificant decrease, and cognitive function were correlated with PSNS activity (Roy's largest root=3.92; P<.01), which is effective for moderate dementia. BML exposure reduced SNS activity and enhanced PSNS activity at night, which consequently affected cognitive function. Furthermore, the light washout intervention markedly increased SNS activity at night. BML therapy may be a useful clinical tool for alleviating the deterioration of cognitive function.

Ultra-short 230 fs laser pulses of 515 nm wavelength were tightly focused into 700 nm focal spots and utilised in opening ~ 0.4 − 1 μm holes in alumina Al2O3 etch masks with 20-50 nm thickness. Such dielectric masks simplify fabrication of photonic crystal (PhC) light trapping patterns for the above-Lambertian performance of high efficiency solar cells. Conditions of laser ablation of transparent etch masks and effects sub-surface Si modifications were revealed by plasma etch- ing, numerical modeling, and minority carrier lifetime measurements. Mask-less patterning of Si is proposed using fs-laser direct writing for dry plasma etch of Si.

This paper describes the use of an open source instrument called LANcube v2 to build a lighting device inventory. The LANcube v2 is and instrument having 5 color sensitive sensors, each on a face of a cube. The instrument can be mounted on a car roof in order to create a map of the artificial light at night while roaming the streets and roads. Based on the temporal variations of the detected signal on various cube’s faces, we developed a method of finding the position in 3D of each lighting device. The lamp spectral types can be determined thanks to the color balance of the raw Red (R) Green (G) Blue (B) and Clear (C) color bands. If one assumes a typical angular photometry of a lighting device with respect to its location, it is possible to estimate its luminous flux. Such information allows us to build a lighting devices inventory of a territory. One advantage of that new method is that it can provide information about the private lighting devices that are always excluded from public lighting inventories. We will compare the inventory extracted with that new methodology with an in situ lamp inventory made for two villages in Canada. This will allow us to emphasize the strengths and limitations of the method by comparing to the ground truth.

Stray light is a critical aspect for high performance optical instruments. When stray light control by design is insufficient to reach the performance requirement, correction by post-processing must be considered. This situation is encountered for example in the case of the Earth observation in-strument 3MI, whose stray light properties are complex due to the presence of many ghosts dis-tributed on the detector array. We implement an iterative correction method and discuss its con-vergence properties. Spatial and field binning can be employed to reduce the computation time but at the cost of a decreased performance. Interpolation of the stray light properties is required to achieve high performance correction. For that, two methods are proposed and tested. The first interpolate the stray light in the field domain while the second applies a scaling operation based on a local symmetry assumption. Ultimately, the scaling method is selected and a stray light reduction by a factor of 58 is obtained at 2σ (129 at 1σ) for an extended scene illumination.

Light-addressable potentiometric sensor (LAPS) is an electrochemical sensor based on the field-effect principle of semiconductor. It is able to sense the change of Nernst potential on the sensor surface, and the measuring area can be controlled by the illumination. Due to the unique light-addressable ability of LAPS, the chemical imaging system constructed with LAPS can realize the two-dimensional image distribution detection of chemical/biomass. In this paper, the advantages of LAPS as sensing unit of microelectrochemical analysis system are summarized. Then, the greatest development of LAPS analysis system is explained and discussed. Especially, this paper focused on the research of ion diffusion, enzymatic reaction, microbial metabolism and droplet microfluidics by using LAPS analysis system. Finally, the development trends and prospects of LAPS analysis system are illustrated.

In the present paper, the so-called Einstein’s causality is scrutinized and proven to be an illusion, a sort of mathematical fallacy. Causality as a well-established universal principle was and is absolutely valid for subluminal, luminal and superluminal signals under any natural and/or artificial circumstances. It is also shown that conceptually special relativity theory (SRT) is inapplicable to superluminality of physical phenomena since SRThas the light speed in vacuum as an upper limiting speed in its own proper domain of applications, and also because SRT is crucially based on the concept of inertial reference frames (IRFs) which are related to each other by Lorentz transformations, that is why the relative velocity of any two IRFs must be smaller than light speed.

The aerosol optical depth is an important indicator of aerosol particle properties and associated radiative impacts. AOD determination is therefore very important to achieve relevant climate modeling. Most remote sensing techniques to retrieve aerosol optical depth are applicable to daytime given the high level of light available. The night represents half of the time but in such conditions only a few remote sensing techniques are available. Among these techniques, the most reliable are moon photometers and star photometers. In this paper, we attempt to fill gaps in the aerosol detection performed with the aforementioned techniques using night sky brightness measurements during moonless nights with the novel CoSQM: a portable, low cost and open-source multispectral photometer. In this paper, we present an innovative method for estimating the aerosol optical depth by using an empirical relationship between the zenith night sky brightness measured at night with the CoSQM and the aerosol optical depth retrieved at daytime from the AErosol Robotic NETwork. Such a method is especially suited to light-polluted regions with light pollution sources located within a few kilometers of the observation site. A coherent day-to-night aerosol optical depth and Ångström Exponent evolution in a set of 354 days and nights from August 2019 to February 2021 was verified at the location of Santa Cruz de Tenerife on the island of Tenerife, Spain. The preliminary uncertainty of this technique was evaluated using the variance under stable day-to-night conditions, set at 0.02 for aerosol optical depth and 0.75 for Ångström Exponent. These results indicate the set of CoSQM and the proposed methodology appear to be a promising tool to add new information on the aerosol optical properties at night, which could be of key importance to improve climate predictions.

Vision is our primary sense as the human eye is the gateway for more than 65% of information reaching the human brain. Today’s increased exposure to different wavelengths and intensities of light from Light Emitting Diodes (LEDs) sources could induce retinal degeneration and accompanying neuronal cell death. Damage induced by chronic phototoxic reactions occurring in the retina accumulates over years and it has been suggested to be responsible for the etiology of many debilitating ocular conditions. In this work, we examined how LED stimulation affects vision by monitoring changes in the expression of death and survival factors as well as microglial activation in LED-induced damage (LID) of the retinal tissue. We found an LED exposure-induced increase in the mRNA levels of major apoptosis-related markers -BAX, Bcl-2, and Caspase-3 and an accompanying wide-spread microglial and Caspase-3 activation. Everyday LED light exposure was accounted for all the described changes in the retinal tissue of mice in this study, indicating that overuse of non-filtered direct LED light can have detrimental effects on the human retina as well.

Improper illumination of cultural heritage buildings and monuments can be a source of enormous light pollution that can have a major impact on the overall environment of the illuminated area. Such lighting can be the result of carelessness or a wrong/badly designed lighting system. This paper presents one of the methodologies that can significantly reduce light pollution, especially the spilt light out of the façade. The methodology is based on using luminaires with specially made shutters with the appropriate silhouette of the object. The shutter is planned with the help of an object photo and sizes measured at the location. The methodology was tested during the renovation of the lighting system of different churches in Slovenia and is described in the example of the Church of St. Thomas near Ptuj, Slovenia. The results showed that the methodology is effective and can significantly reduce light pollution that occurs when such buildings are incorrectly lit.

A typical white-light light-emitting diode (LED) can achieve a sunlight-like spectral profile in the visible spectrum by means of using an optical filter, with an inverted transmission profile to the white LED, fabricated using a deposition coating process. The unfiltered white LED generates white light by mixing light emitted by a blue LED (450 nm) with emission from the yellow phosphorescence excited by the blue light and differs significantly from the characteristics of the full-spectrum natural light. In this study, the spectral characteristics of the filtered LED light can be improved to reach a general color rendering index value (Ra) of 95.6 at the D65.

The ternary Bi2MoO6-reduced graphene oxide (rGO)-TiO2 catalyst were synthesized using a simple hydrothermal method. The improvement of the photocatalytic decomposition efficiency of Bi2MoO6-rGO-TiO2 composite is 92.3% than the pure and binary photocatalyst. The effects of operational parameters like catalyst ratio, the different catalyst, different ratio rGO and different pH, have been analyzed. As prepared ternary photocatalyst is low Photoluminescence and high photocurrent density responsible, it exhibited that photon-induced electron and hole-recombination were suppressed and also charged separation is effective. The present study shows the rGO is an excellent electron transfer performance and enhanced the photocatalytic reaction stability.

The anodic polarization response of magnesium alloy AZ31 was characterized during exposure to aerated 0.1M NaCl solutions with millimolar additions of NaVO₃, Na₃PO₄, Na₂HPO₄, NaF and various pairings to assess their ability to inhibit corrosion kinetics and retard localized corrosion. Each of the candidate inhibitors reduced the corrosion rate of the alloy to some degree. A Na₃PO₄ - NaVO₃ pair produced a powerful inhibiting response decreasing the corrosion rate to about 10^-7 A/cm², which was two orders of magnitude lower than the uninhibited control case. A Bliss Independence assessment indicated that this inhibitor pair acted synergistically. A Na₂HPO₄ - NaVO₃ pair reduced the corrosion rate to 10^-6 A/cm² but was not assessed to be acting synergistically. The NaVO₃ - NaF pair did not reduce the corrosion rate significantly compared to the control case and was an antagonistic pairing. SEM imaging showed film formation due to exposure, which appears to be the origins of the observed inhibition. The resistance to localized corrosion was assessed as the difference in the breakdown potential and the corrosion potential with larger values indicating a lower probability of localized corrosion during free corrosion exposures. Effects of the inhibitors on this characteristic were mixed, but each of the inhibitor pairs yielded potential differences in excess of 100mV. A conceptual conversion coating process based on a mixture of vanadate and phosphate compounds were demonstrated. A fluoride-bearing formulation produced coatings whose total impedance was increased by a factor or 2 compared to an uncoated control. A fluoride-free formulation produced coatings whose corrosion resistance was increased by more than a factor of 3.

Background: Alzheimer’s disease (AD), the most threatening neurodegenerative diseases, is characterized by the loss of memory and language function, an unbalanced perception of space and other cognitive and physical manifestations. Pathology of the AD is characterized by neuronal loss, and the extensive distribution of senile plaques and neurofibrillary tangles (NFTs). The role of environment and the diet in the AD is being studied actively, and nutrition is certainly one of the main factors playing a prominent role in the prevention of neurodegenerative diseases. In this context, the relationship between dementia and wine use/abuse has received increased research interest in recent times, with varying and often conflicting results. Scope and approach: This review aims to critically summarize the most recent studies conducted to clarify the relationship between wine drinking and AD, as well as whether effects are influenced by quantity and/or frequency of drinking. Key findings and Conclusion: Overall, based on the interpretation of various studies, it can be concluded that there is no indication that light to moderate alcohol drinking is detrimental to cognition and dementia, and it is not possible to define whether alcohol could be used as a means to reduce risk of developing AD.

Much remains to be understood for delayed ultraweak photon emission (UPE) from organism in association with oxidative burst following external perturbation, a phenomenon that has been experimented for over three decades. Delayed UPE often decays hyperbolically; yet, it is not uncommon to have delayed UPE that reveals first-order kinetic patterns characterized by single-exponential, double exponential, or multi-exponential changes. Some delayed UPEs also presented transient patterns that are characteristic of second-order responses. A soliton-based photon-storage model has addressed the hyperbolic decaying pattern of delayed UPE; however, there are questions outstanding regarding modeling other non-hyperbolic kinetics as well as the large range of temporal scales of delayed UPE that can vary from 8.5 microseconds to many hours. This work proposes an alternative, phenomenological model-framework for interpreting the various kinetic patterns of delayed UPE following stress. The delayed UPE is considered to be governed by two sequential phases: a stress-transfer phase that transforms the external stress to photo-genesis for emitting photons, and a photon-diffusion phase that transmits the photons emitted by the photo-genesis to the surface of organism for being detected as delayed UPE. Time-resolved photon diffusion analysis reveals that any delayed UPE in organism with a delay time >100ns cannot be addressed by the inherent temporal spread that realistic tissue scattering will cause. A slow stress-transfer phase is thus required to explain the delay time-scales of delayed UPE at a minimum of 8.5 µs as reported experimentally. The stress-transfer phase is hypothesized to carry the following types of responses: single or multiple 1st-order low-pass, single 2nd-order low-pass with various damping factors, and single 2nd-order band-pass with various damping factors. A single 1st–order low-pass response with a time-varying kinetic rate is also analyzed. The responses of these modeled pathways to bolus and step inputs demonstrate that a kinetic pattern other than the exact single-exponential one may have multiple causes.

Three-dimensional (3D) imaging has attracted more and more interests because of its widespread applications, especially in information and life science. These techniques can be broadly divided into two types: ray-based and wavefront-based 3D imaging. Issues such as imaging quality and system complexity of these techniques limit the applications significantly, and therefore many investigations have focused on 3D imaging from depth measurements. This paper presents an overview of 3D imaging from depth measurements, and provides a summary of the connection between these the ray-based and wavefront-based 3D imaging techniques.

Nanoparticles -- regularly patterned or randomly dispersed -- are a key ingredient for emerging technologies in photonics. Of particular interest are scattering and field enhancement effects of metal nanoparticles for energy harvesting and converting systems. An often neglected aspect in the modeling of nanoparticles are light interaction effects beyond classical electrodynamics stemming from electron dynamics in confined and accelerated systems. We give a detailed account on free electron phenomena in metal nanoparticles and discuss analytic expressions, stemming from microscopic and semi-classical theories. These can improve standard computational schemes to produce more reliable results on the optical properties of metal nanoparticles. We combine these solutions into a single framework and study their joint impact on isolated Au, Ag, and Al nanoparticles as well as dimer structures.

Policing duties may inherently be dangerous due to stab, blunt trauma and ballistic threats. The addition of individual light armour vests (ILAVs) has been suggested as a means to protect officers. However, the addition of the extra load of the ILAV may affect officer ability to conduct occupational tasks. The purpose of this study was to determine if wearing any of 3 different ILAVs (ILAV A, ILAV B, & ILAV C) affected occupational task performance when compared to that in normal station wear. A prospective, within-subjects repeated measures design was employed, using a counterbalanced randomization in which each ILAV was worn for an entire day while officers completed a variety of occupationally relevant tasks. These tasks included a victim drag, car exit and 5 meter sprint, step down and marksmanship task. Results showed that performance in each task did not vary between any of the ILAV or normal station wear conditions. There was less variability in the marksmanship task with ILAV B, however. The results suggest that none of the ILAVs used in this study were heavy enough to significantly affect task performance in the assessed tasks when compared to wearing normal station wear.

Wildlands are increasingly lost to human development. Conservation scientists repeatedly call for protecting the remaining wildlands and expanding the land area protected in reserves. Despite these calls, conservation reserves can be eliminated through legislation that demotes their conservation status. For example, legislation introduced to the Congress of the United States recently would demote 29 Wilderness Study Areas (WSAs) from the protections afforded by their existing status. The legislation suggests that the 29 areas are not suitable for a promotion and future inclusion in the National Wilderness Preservation System based on decades-old local evaluations. Local evaluations, notwithstanding, it may be important to consider the value of lands from a national perspective. Without a national perspective, local evaluations alone may overlook the national significance of lands. With this in mind, I used five qualities of wildland value (wildness, light pollution, noise pollution, intactness of mammals, and intactness mammal carnivores of conservation concern) to compare the 29 WSAs to all national parks and wilderness areas located within the contiguous United States. The pool of 29 WSAs were similar to the pool of national parks and wilderness with respect to the five qualities assessed, and some of the WSAs were characterized by higher values than most of national parks and wilderness areas. This analysis demonstrates the national significance of the WSAs targeted for conservation status demotion. Such an approach could be used in future land management legislation and planning to ensure that a national perspective on conservation value is brought to bear on decisions facing federally-managed lands.

Due to the demands of personal travels and entertainments, light airplanes and small business aircrafts are developing rapidly. Light airplane structure is simple; however, it lacks crashworthiness design, especially the considerations on the impact of energy absorption. Therefore, in an event of accident, significant damage to passengers will be usually incurred. Airplanes made of composite materials structurally have high specific strength and good aerodynamic configuration. These materials have become the primary choice for new airplane development. This study mainly explores the topology optimization analysis of the light aircraft’s cockpit made of carbon fiber reinforced composites. This paper compares the compression amounts in the original models of composite material and aluminum alloy fuselages with the models after optimization during the crash-landing, in order to investigate the safety of fuselages made of different materials after structural optimization under the dynamic crashing. This study found that the energy absorbed by the aluminum alloy fuselage during crash-landing is still higher than that by the carbon fiber reinforced composites fuselage. On the other hand, the aluminum alloy fuselage after topology optimization could have an energy absorption capability enhanced by 40%, as compared to the that of the original model of aluminum alloy fuselage.

Antimicrobial resistance (AMR) is a growing concern in healthcare, and the misuse of antibiotics is contributing to the problem. Antimicrobial Stewardship Programs (ASPs) have been proven to help reduce antibiotic consumption, promote appropriate use, and decrease the incidence of AMR and related side effects. In this study, we aimed to evaluate the impact of ASPs on antibiotics consumption and AMR spread in a Southern Italy. Most of the APSs consisted of applying infection control guidelines and WHO recommendations on antibiotic consumption. The results of the study showed that during the study period, the number of hospitalizations increased by 24%, while the total amount of antibiotics administered decreased from 52.1 to 38.6 defined daily doses (DDD) per 100 bed-days. There was also a significant increase in the number of rectal swabs taken to detect carbapenem-resistant Enterobacteriaceae (CRE) and methicillin-resistant Staphylococcus aureus (MRSA), while the positivity rate of these infections decreased significantly. Moreover, the hospital recorded a decrease in the incidence of several infections, including CRPsA, MRSA, PDR, and VanA infections. This study provides further evidence that ASPs can be effective in reducing antibiotic consumption and preventing the spread of AMR. By promoting the appropriate use of antibiotics and implementing infection control measures, we can help preserve the effectiveness of these life-saving drugs and promote better patient outcomes. However, more efforts are needed to improve healthcare practices and reduce related costs. In conclusion, we urge healthcare providers to implement ASPs in their institutions and help combat the growing threat of AMR. By doing so, we can ensure that antibiotics remain effective for future generations.

The control of stereo-, regio-, and chemo-selectivity in transition-metal-catalyzed coupling reactions is a key topic in organic synthesis. Several methods for controlling selectivity have been reported thus far. On the other hand, the reduction of the catalyst loading in the reaction is one of the most important issues in organic synthesis from the standpoint of green sustainable chemistry. As another advantage of reducing the catalyst loading, the expression of the reaction selectivity and the substituent effect caused by the reduction of the catalyst loading to the parts-par-million (ppm) level in various catalytic reactions is presented herein.

Nano-emulsions of essential oils (EO) and their chemical constituents are promising raw materials for the ecological control of Tribolium castaneum. Curcuma longa Linn is a plant known for the properties of its rhizome which is used in food, health and hygiene products. Its leaves are by-products with no commercial value, but with unexplored bioactive volatile constituents. This study aims to evaluate the repellency of nano-emulsions containing the EO from leaves of C. longa or its three main chemical constituents against T. castaneum. The representative mixture of EO extracted in four different months showed p-cymene (26.0%), 1,8-cineole (15.1%) and terpinolene (15.5%) as major compounds. Nano-emulsions of EO (HLB 16.7), terpinolene (HLB 15.0), 1,8-cineole (HLB15.0) and p-cymene (HLB 15.0) were repellent at concentrations of 11 μg/cm2 (EO, terpinolene and p-cymene) and 1.1 μg/cm2 (1,8-cineole). The EO nano-emulsion droplet size increased linearly over time, remaining below 300 nm for 35 days and below 600 nm for 80 days. The EO nano-emulsion proved to be a green alternative to synthetic pesticides, as it was safe against the bioindicator Chlorella vulgaris. Terpinolene, 1,8-cineol and p-cymene were able to inhibit the enzyme telomerase from T. castaneum in an in silico assay, which may explain the repellency of these samples. This study provides ideas for the utilization of EO from leaves of C. longa as raw material of new environmentally friendly plant-derived nanobiopesticides.

Primates have an unparalleled ability to produce a wide range of dexterous movements, each sensitive to context and robust to perturbation. Recent progress in understanding the neural basis of movement generation comes from two largely independent ideas, “Optimal Feedback Control” and “Neural Dynamical Systems”. The optimal control framework was largely inspired by research programs from the ‘80s showing that the brain doesn’t seem to plan a simple desired movement trajectory, but instead produces movements by transforming sensory information into motor output that satisfies an optimality criterion. The more recent idea that the motor cortex acts as a dynamical system came about only as it became possible to analyze large numbers of simultaneously recorded single neurons. These two framings of the motor system have been largely incommensurate, neither able to contribute much to the understanding of the other. In this review, we reconcile these two views into a single model we call “Dynamical Feedback Control”. We propose that the dynamics in the motor cortex emerge from a sensorimotor transformation that couples the motor cortex to sensory input from the periphery, and to contextual inputs from other cortical and subcortical areas. Dynamics in motor cortex can be thought to approximate gains of a feedback controller, and by moving the neural state to different regions of state space, the motor system can rapidly alternate between different controllers. The DFC framework presents a new lens to interpret neural dynamics, and to understand how ensembles of neurons generate flexible and responsive patterns of muscle activity.

The aim of this paper is to examine the beneficial impact of feedback information in the dynamics of production-inventory control systems. Two production-inventory control system models are analyzed: APIOBPCS and 2APIOBPCS models. The simulation-based experiment designs were conducted by using the state-space equations of the two models. The bullwhip effect as measured by the variance ratio between the order rate and the consumption rate, and inventory responsiveness as measured by the Integral of Absolute Error between the actual and the target levels of inventory, are two metrics used to evaluate the performance of the production-inventory control system in response to a random customer demand. To ensure that both models work under optimal performance, multi-objective particle swarm optimization (MOPSO) is employed to address the problem of tuning the controller’s parameters. The simulation results show the 2APIOBPCS model outperforms the APIOBPCS model at achieving the desired bullwhip effect and being able to provide better inventory responsiveness. The improvement in the inventory responsiveness becomes more significant when the system operates under mismatched lead time and/or an initial condition.

A high-level control algorithm capable of generating position and torque references from surface electromyography signals (sEMG) has been designed. It is applied to a shape memory alloy (SMA) actuated exoskeleton used in active rehabilitation therapies for elbow joints. The sEMG signals are filtered and normalized according data collected online during the first seconds of~therapy sessions. The control algorithm uses the sEMG signals to promote active participation of patients during the therapy session. In order to generate the position reference pattern with good precision, the sEMG normalized signal is compared with a pressure sensor signal to detect the intention of each movement. The algorithm has been tested in simulations and with healthy people for control of an elbow exoskeleton in flexion–extension movements. The results indicate that sEMG signals from elbow muscles in combination with pressure sensors that measure arm–exoskeleton interaction can be used as inputs for the control algorithm, which adapts the reference for exoskeleton movements according a patient's intention.

Mozambique is endemic to aflatoxigenic Aspergillus but the country has to heavily rely on foreign research to deduct what is happening locally. There is some information produced by local scholars and institutions but it needs to be “tied” together. This review briefly synthetizes the country’s major findings in relation to the toxin’s etiology, epidemiology, detection and control, discussing and meta-analyzing them as far as they allow. The causes and foods affected are the same as in most tropical countries, the toxin is widespread and the level of exposure is high. Regarding the control, it is still marginal but some institutions have driven efforts in this direction. Learning from other countries is still the best approach to take, as the solutions are probably the same for most places.

This paper builds on previous work introducing the Secure Remote Update Protocol (SRUP)—a secure communications protocol for Command & Control applications in the Internet of Things, built on top of MQTT. This paper builds on the original protocol, and introduces a number of additional message types: adding additional capabilities to the protocol. We also discuss the difficulty of proving that a physical device has an identity corresponding with a logical device on the network, and propose a mechanism to overcome this within the protocol.

Electric tractors have many advantages, including high torque, excellent controllability, energy efficiency, simple structure, and electric interface for expansion. However, a significant limitation lies in their endurance. This study presents the design of an extended-range power supply system to ensure continuous endurance of electric tractor. The objective is to provide a continuous power source for our self-developed electric tractor while preserving the benefits of electric propulsion. Extended-range power systems utilize a primary mover, typically an oil-fueled internal combustion engine, to drive the generator for electricity generation, and the generated AC form electricity is subsequently converted into stable DC bus voltage by a power electronic converter. The hardware and control design of the extended-range power supply system have been finalized and validated through experimental trials. Results demonstrate the system’s capability to sustain a stable DC bus voltage amidst disruptions such as sudden load shifts and fluctuations in prime mover speed. Even with 50% sudden load change, the voltage drop is within 12% and could recover to ±3% within 4 seconds. The range extender can be used alone without battery to power the electric tractor, or it can used in parallel with other extended-range extenders or battery thanks with the droop control ability for power sharing.

Whilst Model Reference Adaptive Control theory provides mathematical techniques for achieving the performance of the system without undue dependence upon dynamic systems models, its applicability may not be suitable for systems that are crucial to safety due to suboptimal transient and error convergence performance. In this article, our approach enhances the performance of MRAC by utilizing a Generalized Dynamic Inversion (GDI). Two control actions are permitted under the GDI control law. One control is the particular part that is responsible for enforcing the reference system-constrained behaviors. Another control action is carried out by the control law’s auxiliary component and is incorporated into the standard MRAC control law. This augmented part is referred to as a null control vector, and it is used to enhance the performance of MRAC. The classic MRAC control law, when supplemented with a null vector term consisting of an adaptive gain that changes in response to tracking errors, forces the dynamical system to behave similarly to the reference model. This null vector, in particular, restricts the oscillation intensity of the tracking errors, which is employed to generate the adaptive parameters. It is demonstrated that this critical element of our approach enhances transient performance and ensures that error dynamics vanish asymptotically. Extensive simulations have been conducted to prove the efficacy of the proposed method.

This paper proposes a novel approach called Multi-strategy Improved Chaotic Whale fused with Perturbation Observation method (IWOA-PO) for Maximum Power Point Tracking (MPPT) con-trol, to address the challenge of low efficiency in photovoltaic (PV) power generation under local shadows, according to the features of whale optimization algorithm (WOA) and perturbation observation (P&O) method. In the early stage of control algorithm, IWOA is used for global search to quickly locate the position of the Maximum Power Point (MPP). In the later stage of control algorithm, P&O is used for fine-grained local search to quickly, accurately and low oscillation track the position of the global maximum power point (GMPP). In order to verify the correctness, the tracking performance of IWOA-PO is comprehensively compared with WOA-PO、WOA、PSO under four conditions including uniform illumination, static partial shade, dynamic irradiance mutation and sudden changes in temperature and irradiance. In the above four conditions, the IWOA-PO algorithm has faster convergence and less power oscillations compared to the re-maining three algorithms, indicating that the IWOA-PO algorithm is effective. Finally, a physical verification experiment process is built to verify the correctness and effectiveness of the algorithm proposed in this paper.

Previous control methods developed by our research team cannot satisfy the high-accuracy requirements of unmanned surface vessel (USV) path-tracking during bathymetric mapping because of the excessive overshoot and slow convergence speed. For this reason, this study developed an adaptive fuzzy integral-derivative line-of-sight (AFIDLOS) guidance law for USV path-tracking control. Integral and derivative terms were added to counteract the effect of the sideslip angle, with which the USV could be quickly guided to converge to the planned path for bathymetric mapping. To obtain a high-accuracy of the look-ahead distance, a fuzzy control method was proposed. The proposed method was verified using simulations and outdoor experiments. The results demonstrate that the AFIDLOS guidance law can reduce the overshoot by 79.85%, shorten the settling time by 55.32% in simulation experiments, and reduce the average cross-track error by 10.91%, and can ensure a 30% overlap of neighboring strips of bathymetric LiDAR outdoor mapping when compared with the traditional method.

The need for industrial and commercial machinery to maintain high torque while accurately following a variable angular speed is increasing. To meet this demand, induction motors (IMs) are commonly used with variable speed drives (VSDs) that employ a field-oriented control (FOC) scheme. Over the last thirty years, IMs have been replacing independent connection direct current motors due to their cost-effectiveness, reduced maintenance needs, and increased efficiency. However, IMs and VSDs exhibit nonlinear behavior, uncertainties, and disturbances. This paper proposes a robust combined adaptive passivity-based control (CAPBC) for this class of nonlinear systems that applies to angular rotor speed and stator current regulation inside an FOC scheme for IMs´ VSDs. It uses general Lyapunov-based design energy functions and adaptive laws with σ-modification to assure robustness after combining control and monitoring variables. Lyapunov’s second method and Barbalat Lemma prove that the control and identification error tends to be zero over time. Moreover, comparative experimental results with standard Proportional Integer controller (PIC) and direct APBC, show the proposed CAPBC effectiveness and robustness under normal and changing conditions

The purpose of this study is to investigate the impact of the voltage drop of a three-phase voltage source inverter in driving brushless motors. This study also proposes an enhanced Field Oriented Control scheme that accounts for the inverter voltage drop enabling efficient drive at very low motor-speeds. Experimental results are provided to verify the theoretical study and the proposed control scheme.

Wind power generation is one of the mainstream renewable energy resources. Voltage stability is as important as the frequency stability of a power system with a high penetration of wind power generation. The advantages of high-voltage direct current (HVDC) transmission systems become more significant with the increase of both installed capacity and transmission distance in offshore wind farms. Therefore, this study discusses about various voltage control methods for wind turbines and HVDC transmission systems. First, various voltage control methods of a wind farm were introduced, and they include QV control and voltage droop control. The reactive power of a wind turbine varies with active power, while the active power from each wind turbine may be different owing to wake effects. Thus, QV and voltage droop control with varying gain values were also discussed in this paper. Next, the voltage control methods for a HVDC transmission system, such as power factor control, voltage control, and Vac-Q control, are also summarized and tested in this study. When a three-phase short circuit fault occurs or a suddan reactive power load increases, the system voltage would drop immediately. Thus, various voltage control methods for wind turbines or HVDC can make the system's transient response more stable. Therefore, this study implemented the simulation scenarios, including a three-phase short circuit fault at the point of common coupling (PCC) or a sudden increase of reactive power load, and adopted various voltage control methods, which aims to verify whether additional voltage control methods are effective to improve the performance of transient voltage.

The paper aims to study the workflow of the detection center of stealthy attacks on industrial installations that generate increase in energy consumption while avoiding triggering fault detection and damaging the installation. Such long-lasting attacks on industrial facilities make production more expensive and less competitive. We present the concept of the remote detection system of cyberattacks directed at maliciously changing the controlled variable in an industrial process air conditioning system. The monitored signals are gathered at the PLC-controlled installation and sent to the remote detection system, where the discrepancies of signals are analyzed based on the Control Performance Assessment indices. The results of performed tests prove the legitimacy of the adopted approach.

Attitude control of a novel regional truss-braced wing aircraft with low stability characteristics is addressed in this paper using Reinforcement Learning (RL). In recent years, RL has been increasingly employed in challenging applications, particularly, autonomous flight control. However, a significant predicament confronting discrete RL algorithms is the dimension limitation of the state-action table and difficulties in defining the elements of the RL environment. To address these issues, in this paper, a detailed mathematical model of the mentioned aircraft is first developed to shape an RL environment. Subsequently, Q-learning, the most prevalent discrete RL algorithm will be implemented in both the Markov Decision Process (MDP), and Partially Observable Markov Decision Process (POMDP) frameworks to control the longitudinal mode of the air vehicle. In order to eliminate residual fluctuations that are a consequence of discrete action selection, and simultaneously track variable pitch angles, a Fuzzy Action Assignment (FAA) method is proposed to generate continuous control commands using the trained Q-table. Accordingly, it will be proved that by defining an accurate reward function, along with observing all crucial states (which is equivalent to satisfying the Markov Property), the performance of the introduced control system surpasses a well-tuned Proportional–Integral–Derivative (PID) controller.