Direct Sensor Research Articles

Structures of the multi-domain oxygen sensor DosP: remote control of a c-di-GMP phosphodiesterase by a regulatory PAS domain.

The heme-based direct oxygen sensor DosP degrades c-di-GMP, a second messenger nearly unique to bacteria. In stationary phase Escherichia coli, DosP is the most abundant c-di-GMP phosphodiesterase. Ligation of O2 to a heme-binding PAS domain (hPAS) of the protein enhances the phosphodiesterase through an allosteric mechanism that has remained elusive. We determined six structures of full-length DosP in its aerobic or anaerobic conformations, with or without c-di-GMP. DosP is an elongated dimer with the regulatory heme and phosphodiesterase separated by nearly 180 Å. In the absence of substrate, regardless of the heme status, DosP presents an equilibrium of two distinct conformations. Binding of substrate induces DosP to adopt a single, ON-state or OFF-state conformation depending on its heme status. Structural and biochemical studies of this multi-domain sensor and its mutants provide insights into signal regulation of second-messenger levels.

Wind Source Localization System Based on a Palm-Sized Quadcopter

In this study, we implemented a compact wind direction sensor on a palm-sized quadcopter to achieve wind source localization (WSL). We designed an anemotaxis algorithm based on the sensor data and experimentally validated its efficacy. Anemotaxis refers to the strategy of moving upwind based on information on the wind direction, which is essential for tracing odors propagating through the air. Despite the limited research on quadcopter systems achieving WSL directly through environmental wind measurement sensors, debate remains regarding the relationship between sensor placement and the anemotaxis algorithm. Therefore, we experimentally investigated the placement of a wind direction sensor capable of estimating wind source direction even when propellers are rotating. Our findings demonstrated that placing the sensor 50 mm away from the enclosure of the quadcopter allowed accurate wind direction measurement without being affected by wake disturbances. Additionally, we constructed an anemotaxis algorithm based on wind direction and speed data, which we integrated into the quadcopter system. We confirmed the ability of the quadcopter to execute anemotaxis behavior and achieve WSL irrespective of environmental wind strength through wind source localization experiments.

Assessment of indoor radon concentration in the dwellings of the industrial areas of Kannur District, Kerala.

All organisms on the earth-crest are exposed to natural background radiation since the evolution of the earth, as many environmental matrices such as soil, air, water bodies, vegetation, etc., act as the sources of natural radioactivity. The present study deals with the evaluation of indoor concentration of 222Rn (radon) in different dwellings with various construction materials used for the roof and floor in the industrial sites of Kannur district, Kerala. A pinhole-based dosemeter coupled with LR-115 Solid State Nuclear Track Detector and Direct Radon Progeny Sensor (DRPS) were respectively used for the measurement of indoor radon concentration and equilibrium equivalent concentration of radon. The indoor radon concentrations were found to vary from 102.30 Bqm-3 to 184.75 Bqm-3 and the values were within the recommended limits provided by International Commission on Radiological Protection (ICRP). The annual effective doses and excess lifetime cancer risks were observed in the range of 2.58-4.66 mSvy-1 and 7.68×10-3-15.60×10-3, respectively, and both exceed the world average values recommended by United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) 2000. The study shows that, the houses with marble floors and concrete roofs have comparatively higher values of radon concentration, which indicates the significant contribution of construction materials to the enhanced radiation levels inside the dwellings.

A new hybrid genetic algorithm with tabu search for solving the temporal coverage problem using rotating directional sensors

AbstractOne of the most important problems in directional sensor networks is coverage problem. The coverage can be measured in two ways: positional or temporal. In temporal coverage, the directional sensors rotate periodically round themselves in a repetitive process. Thus, in each time slot, those targets that are positioned within the sensor nodes radius receive their desired coverage. In this model, if a target is left uncovered, it is said that the target has remained in darkness. The main task defined for the temporal coverage model is the minimization of the total dark time for all the targets in the network. This problem has been solved by greedy‐based algorithms in last studies. Greedy‐based algorithms are able to solve the temporal coverage problem in real time. Remember that the performance of greedy algorithms is extremely dependent on the closeness of optimal solution and initial candidates. For this reason, greedy algorithms may obtain local minima due to heuristic search. As far as we know meta‐heuristic algorithms have not been used in past researches to solve such problems. For solving this problem, in this paper two algorithms were developed, GA‐based and hybridized model comprising genetic algorithms and tabu search. A new model was suggested for the chromosome in genetic algorithm. To evaluate the performance of the developed algorithms, they were compared with randomized scenario and greedy‐based algorithm presented in last studies. For better comparison, several parameters, including total dark time, number of sensors, number of targets, sector angle, sensing range were taken into account. The results obtained from the comparison of the algorithms indicated that the developed algorithms are effective in solving the temporal coverage problem in terms of minimizing the total dark time of the targets.

Refractive insensitive directional bend sensor based on specialty microstructure optical fiber with dumbbell shape core

With the development of information society, more and more special occasions are calling for a wide range of sensors with special properties. In this work, a refractive index insensitive directional bend sensor is proposed based on a specialty microstructure optical fiber with dumbbell shape core, which works as a dual core fiber (DCF). Firstly, this specialty microstructure optical fiber with dumbbell shape core has been fabricated with self-pressurised drawing technique. Then, it has been constructed as a Mach-Zehnder interferometer (MZI) sensor. Consequently, its bend sensing characteristics has been investigated from both theory and experiment. The response of the proposed sensor to the bending evidently displays the directional dependence. In the bending along x direction, the interference peak wavelength is almost insensitive to the curvature. But the transmission is sensitive, which almost obeys the exponential function. Correspondingly, in the bending along y direction the wavelength almost linearly varies with curvature, giving out an averaged sensitivity of 2.44 nm/m−1 in the curvature range of 0–3.79 m−1. But the peak transmission fluctuates without typical principle. In addition, the response of the proposed sensor to the refractive index variation has been checked. It is found that the peak wavelength is almost insensitive to the change of refractive index from 1.33 to 1.45, and the peak transmission fluctuates without clear principle. All these results demonstrate that the proposed sensor has great potential for future internet of things (IoT) applications.

Comparison of Barrier Surveillance Algorithms for Directional Sensors and UAVs.

Border surveillance and the monitoring of critical infrastructure are essential components of regional and industrial security. In this paper, our purpose is to study the intricate nature of surveillance methods used by hybrid monitoring systems utilizing Pan-Tilt-Zoom (PTZ) cameras, modeled as directional sensors, and UAVs. We aim to accomplish three occasionally conflicting goals. Firstly, at any given moment we want to detect as many intruders as possible with special attention to newly arriving trespassers. Secondly, we consider it equally important to observe the temporal movement and behavior of each intruder group as accurately as possible. Furthermore, in addition to these objectives, we also seek to minimize the cost of sensor usage associated with surveillance. During the research, we developed and analyzed several interrelated, increasingly complex algorithms. By leveraging RL methods we also gave the system the chance to find the optimal solution on its own. As a result we have gained valuable insights into how various components of these algorithms are interconnected and coordinate. Building upon these observations, we managed to develop an efficient algorithm that takes into account all three criteria mentioned above.

Usage and structural health monitoring systems in military tactical transport aircraft

The variability of use in the military tactical transport aircraft is not always well captured in the intended use declared by the operators. On the other hand, the computers installed in the aircraft are already collecting huge amount of data that can be downloaded on ground with no additional burden. With the properly data analysis and management on ground, and by using the existing flight physics models of the aircraft or by training neuronal networks it is possible to use the data to obtain relevant information. Such as usage figures, detect potential overloads, obtain loads and stresses several times by second. Those loads and stress time histories can then use to re-calculate the fatigue and crack propagation is the same way as per certification in a cycle-by-cycle basis, then re-evaluate the maintenance to optimized it according to real use of the aircraft. Produce operational recommendations and perform prognosis analysis considering the past and intended use in the future. On the other hand, for local areas prone to accidental damage, direct sensor measurements can be used for damage monitoring.

Photosystems and photoreceptors in cyanobacterial phototaxis and photophobotaxis.

Cyanobacteria move by gliding motility on surfaces toward the light or away from it. It is as yet unclear how the light direction is sensed on the molecular level. Diverse photoreceptor knockout mutants have a stronger response toward the light than the wild type. Either the light direction is sensed by multiple photoreceptors or by photosystems. In a study on photophobotaxis of the filamentous cyanobacterium Phormidium lacuna, broad spectral sensitivity, inhibition by 3-(3,4-dichlorophenyl)-1,1-dimethylurea (DCMU), and a highly sensitive response speaks for photosystems as light direction sensors. Here, it is discussed whether the photosystem theory could hold for phototaxis of other cyanobacteria.

Directional bending sensor based on Mach-Zehnder interferometer formed by side-polished multimode fiber

This work proposes a fiber bending sensor based on the Mach-Zehnder interferometer (MZI) constructed using a side-polished multimode fiber (MMF) with bending direction recognition. The sensor is fabricated by directly fusing a section of side-polished MMF sandwiched between two no-core fibers (NCFs) to an input and output single-mode fibers (SMFs). As the applied curvature varies from 0 m−1 to 1.64 m−1, the transmission spectra of the sensor exhibit distinct and linear wavelength shift in opposite directions. The maximum sensitivity observed in 0° and 180° bending is 3.252 nm/m−1 and −1.146 nm/m−1, respectively. The maximum temperature sensitivity is 0.0621 nm/°C and this effect can be compensated by using the sensitivity matrix. The advantages of the proposed sensor include its ability to accurately quantify the direction and magnitude of bending, temperature crosstalk elimination, and cost-effectiveness. These features make the sensor highly desirable for a wide range of practical directional bending applications, such as medical wearable devices for human joint range of motion monitoring.

Flight tests results of a Fiber Bragg Gratings based ice sensor

Icing has been an aeronautical industry problem for safety and for energy consumption save from the beginning of aviation. It affects the safety reducing the lift, decreasing the stall angle of attack, affecting the aircraft stability and reducing the control efficiency. The European project SENS4ICE (2019–2023) introduces a new technology based on hybridization of different detection techniques, combining indirect ice sensing with direct, using atmospheric and ice accretion sensors. In the present work a study about a Fiber Optic Detector based on latent heat that uses a Fiber Bragg Grating for measuring the surface temperature. The Fiber Optic Detector (FOD) was tested in a SAFIRE Flight Testing Platform ATR42 during 40 h of Flight testing, having Liquid Water encounters in all flights. The sensor performance and its ability for measuring the icing severity is evaluated in the paper, showing results in a representative Flight test.During Flight Test, different icing conditions were seen, adapting the detection and severity evaluations to the data seen with other reference atmospheric sensors. For ice detection Discrete Wavelet Transform (DWT) was used using different levels in order to detect all the possible events during the Flight test. The DWT ice severity assessment results were compared with a Messinger Model and with the DLR Nevzorov data in order to evaluate the precision and the sensor performance.

Engineering of Lactate Oxidase and Dehydrogenase for Development of Direct Electron Transfer Type Lactate Sensor and Application for Multiplexed Biosensor System

Engineering of Lactate Oxidase and Dehydrogenase for Development of Direct Electron Transfer Type Lactate Sensor and Application for Multiplexed Biosensor System

Anti-crosstalk fiber-optic directional torsion sensor via intensity-modulated Lyot filter

In this paper, a fiber-optic directional torsion sensor based on the intensity modulated Lyot filter is completed to alleviate the crosstalk from ambient temperature and axial strain. The transmission is analyzed and compared with the varied twisted length. The experimental results show that the torsion response of 1.18 dB/° can be achieved by the 45° incident angle and 10-cm twisted length, with tiny wavelength shift (∼0.012 nm/°) and minimum range of π-phase jumping. Meanwhile, the crosstalk is well compressed within 0.006°/με and 0.23°/°C owing to ultralow axial-strain and temperature responses. In addition, an in-field test is performed electrically and the detection limit of 0.08° is witnessed experimentally.

Dynamic feature-based deep reinforcement learning for flow control of circular cylinder with sparse surface pressure sensing

This study proposes a self-learning algorithm for closed-loop cylinder wake control targeting lower drag and lower lift fluctuations with the additional challenge of sparse sensor information, taking deep reinforcement learning (DRL) as the starting point. The DRL performance is significantly improved by lifting the sensor signals to dynamic features (DFs), which predict future flow states. The resulting DF-based DRL (DF-DRL) automatically learns a feedback control in the plant without a dynamic model. Results show that the drag coefficient of the DF-DRL model is 25 % less than the vanilla model based on direct sensor feedback. More importantly, using only one surface pressure sensor, DF-DRL can reduce the drag coefficient to a state-of-the-art performance of approximately 8 % at Reynolds number $(Re) = 100$ and significantly mitigates lift coefficient fluctuations. Hence, DF-DRL allows the deployment of sparse sensing of the flow without degrading the control performance. This method also exhibits strong robustness in flow control under more complex flow scenarios, reducing the drag coefficient by 32.2 % and 46.55 % at $Re =500$ and 1000, respectively. Additionally, the drag coefficient decreases by 28.6 % in a three-dimensional turbulent flow at $Re =10\,000$ . Since surface pressure information is more straightforward to measure in realistic scenarios than flow velocity information, this study provides a valuable reference for experimentally designing the active flow control of a circular cylinder based on wall pressure signals, which is an essential step toward further developing intelligent control in a realistic multi-input multi-output system.

Lipid phase separation impairs membrane thickness sensing by the Bacillus subtilis sensor kinase DesK.

The B. subtilis des system is a prime model for direct molecular membrane thickness sensor and, as such, has been well studied in vitro. Our study shows that our understanding of its function in vivo and its importance under temperature and antibiotic stress is still very limited. Specifically, our results suggest that (i) the des system senses very subtle membrane fluidity changes that escape detection by established fluidity reporters like laurdan; (ii) membrane thickness sensing by DesK is impaired by phase separation due to partitioning of the protein into the fluid phase; and (iii) fluidity adaptations by Des are too subtle to elicit growth defects under rigidifying conditions, raising the question of how much the des system contributes to adaptation of overall membrane fluidity.

Optimization Method for Node Deployment of Closed-Barrier Coverage in Hybrid Directional Sensor Networks

Optimization Method for Node Deployment of Closed-Barrier Coverage in Hybrid Directional Sensor Networks

Mastering broom‐like tools for object transportation animation using deep reinforcement learning

SummaryIn this paper, we propose a deep reinforcement‐based approach to generate an animation of an agent using a broom‐like tool to transport a target object. The tool is attached to the agent. So when the agent moves, the tool moves as well.The challenge is to control the agent to move and use the tool to push the target while avoiding obstacles. We propose a direction sensor to guide the agent's movement direction in environments with static obstacles. Furthermore, different rewards and a curriculum learning are implemented to make the agent efficiently learn skills for manipulating the tool. Experimental results show that the agent can naturally control the tool with different shapes to transport target objects. The result of ablation tests revealed the impacts of the rewards and some state components.

Microwave Methods and Technologies for Monitoring Electrical Activity of the Skin

The paper presents the analysis of the existing solutions for measuring the electrical activity of the skin using traditional methods, which include the use of direct current sensors, and also proposes new promising solutions related to the use of sensing elements based on slow wave systems. The questions of practical realization of electrodes, in particular materials and topologies providing mechanical strength and ergonomics of elements of wearable devices are considered. It is shown that the use of microwave sensors allows to increase the sensitivity of the device in comparison with the existing analogs on direct current, and also possess the desired mechanical properties, allowing them to be resistant to deformations.

Non‐Hermitian Broadside Coupled Split Ring Resonators with Directional Sensitivity

AbstractDirectional radiofrequency (RF) sensing, also known as radio direction finding, is essential in various applications that involve localizing RF sources. However, existing RF sensing technologies face challenges due to their large antenna sizes and complex RF signal processing circuits, which hinder the realization of miniaturized subwavelength direction sensors. In this article, a non‐Hermitian broadside coupled split ring resonators (BC‐SRRs) are presented, which can identify the direction of an incident RF signal with angles ranging from 0° to 180°. The non‐Hermitian Hamiltonian of the system, which can be interpreted by the temporal coupled mode theory, gives rise to asymmetric resonant modes of the BC‐SRRs. The asymmetry allows the direct measurement of RF wave incident angle by probing the resonant strength of the two BC‐SRRs. For the proof of concept, a one‐stage Dickson voltage multiplier is employed to rectify the RF signals and demonstrate angle sensing ability by relating the rectified voltage to the incident angle. The results showcase the potential of the proposed technique using non‐Hermitian BC‐SRRs as a pathway toward subwavelength antenna‐based radio direction finding.

Liquid Plug Motion Noninvasive Detecting in Opaque Microchannels via Grating Electrodes‐Based Liquid‐Solid Nanogenerator

AbstractThe precision in controlling fluid flow is crucial for the efficiency of microchannel devices. Consequently, it is essential to monitor the fluid within microchannels in real time. However, the microchannel flow's susceptibility to disturbance and small size present challenges in sensing. A Liquid‐Solid Triboelectric Nanogenerator (TENG) with grating electrodes is proposed for non‐invasive sensing of liquid plug movements in microchannels and is suitable for use with opaque channels. This sensor operates on the principle of initiating multiple pulse signals via grating electrodes. And analyze the motion of the liquid plug by the time difference between the signal peaks. It facilitates the measurement of liquid plug count, average speed, average acceleration, and the detection of flow direction. The liquid plug counters, and flow direction sensors yielded clear and distinguishable signals. The liquid plug average speed sensor achieves a 95% accuracy rate, and the acceleration sensor accurately distinguishes speed trends of the liquid plug with more than 85% precision. Grating electrodes are effectively employed for motion sensing. Analyzing the motion of an object by the time difference between voltage peaks offers greater stability than voltage magnitude analysis. Four portable prototypes are designed to make them applicable for fluid sensing in microchannel devices.

A Stable and Highly Sensitive Directional Torsion Sensor Based on a Helical Double Cladding Microstructured Multicore Fiber

A Stable and Highly Sensitive Directional Torsion Sensor Based on a Helical Double Cladding Microstructured Multicore Fiber