Anti-noise UWFBG-array enhanced DAS system using double-pulse-based time-domain adaptive delay interference: publisher's note.

This publisher's note contains a correction to Opt. Lett.48, 1814 (2023)10.1364/OL.486149.

Anti-noise UWFBG-array enhanced DAS system using double-pulse-based time-domain adaptive delay interference.

An anti-noise interrogation technique for ultra-weak fiber Bragg grating (UWFBG)-based distributed acoustic sensing (DAS) systems is proposed and demonstrated using double-pulse-based time-domain adaptive delay interference. This technique breaks the limitation that the optical path difference (OPD) between the two arms of the interferometer should be completely matched with the entire OPD between the adjacent gratings in the traditional single-pulse system. The length of the delay fiber in the interferometer can be reduced, and the double-pulse interval can adapt flexibly to the UWFBG array with different grating spacing. The acoustic signal is restored accurately when the grating spacing is 15 m or 20 m by the time-domain adjustable delay interference. Moreover, the noise induced by the interferometer can be suppressed significantly as compared to using a single pulse, and above 8-dB signal-to-noise ratio (SNR) enhancement can be obtained without any extra optical devices when the noise frequency and the vibration acceleration are below 100 Hz and 0.1 m/s2, respectively.

A Two-To-One Deep Learning General Framework for Image Fusion.

The image fusion algorithm has great application value in the domain of computer vision, which makes the fused image have a more comprehensive and clearer description of the scene, and is beneficial to human eye recognition and automatic mechanical detection. In recent years, image fusion algorithms have achieved great success in different domains. However, it still has huge challenges in terms of the generalization of multi-modal image fusion. In reaction to this problem, this paper proposes a general image fusion framework based on an improved convolutional neural network. Firstly, the feature information of the input image is captured by the multiple feature extraction layers, and then multiple feature maps are stacked along the number of channels to acquire the feature fusion map. Finally, feature maps, which are derived from multiple feature extraction layers, are stacked in high dimensions by skip connection and convolution filtering for reconstruction to produce the final result. In this paper, multi-modal images are gained from multiple datasets to produce a large sample space to adequately train the network. Compared with the existing convolutional neural networks and traditional fusion algorithms, the proposed model not only has generality and stability but also has some strengths in subjective visualization and objective evaluation, while the average running time is at least 94% faster than the reference algorithm based on neural network.

Tillage activates iron to prevent soil organic carbon loss following forest conversion to cornfields in tropical acidic red soils.

Previous studies have shown that deforestation and planting of corn resulted in the loss of soil organic carbon (SOC). However, this is not inevitable in regions with acidic red soil. We selected six cornfields that have been planted for 34 years and adjacent forest plots in southwest China. Using a structural equation model, we identified the SOC contents and 42 soil environmental factors in 11 soil layers that are conducive to SOC storage, and evaluated their relative weights hierarchically (0-40, 40-100, and 100-140 cm). Our results surprisingly indicated that after forest had been converted into cornfield, the SOC density did not change in any layer. In acidic red soil, reactive iron (Feo), soil water content, nitrogen, and pH were the main soil environmental factors that affected the storage of SOC. In the 0-40 cm soil layer, compared to forests, the contribution of Feo in cornfields increased significantly (by 11.65%), due to farming promoting the activation of iron, while the contribution of nitrogen decreased significantly (by 9.65%). In the 100-140 cm soil layer, the contribution of soil environmental factors was similar to that in the forest system, but the pH in cornfields increasing significantly (by 21.5%) may result from the leaching of hydrogen ions. Although the cultivation of cornfields caused a loss of nitrogen in the 0-40 cm soil layer, the increase in Feo promoted combination of iron and soil organic carbon, avoiding the soil layer from SOC loss.

What Drives the Trickle-Down Effect of Calling Orientation From Supervisors to Subordinates? The Perspective of Social Learning Theory.

Despite an increase in research on calling orientation, few studies have investigated its antecedents. Drawing on social learning theory, we hypothesized that subordinates' perceptions of their supervisor's role modeling mediate the relationship between supervisor's and subordinates' calling orientations. Supervisor's organizational status is supposed to augment the trickle-down process for calling orientation. We used multilevel modeling to test these hypotheses in a sample of 738 subordinates nested in 77 work teams in Chinese firm. We found that supervisor's calling orientation was positively related to subordinate's calling orientation and that the relationship was fully mediated by subordinates' perceptions of role modeling. Additionally, the relationship between supervisor's calling orientation and subordinates' calling orientation via role modeling was moderated by supervisor's organizational status at the second stage.

Fiber Bragg Grating Displacement Sensor with High Abrasion Resistance for a Steel Spring Floating Slab Damping Track.

This paper presents a fiber Bragg grating (FBG) displacement sensor with high abrasion resistance for displacement monitoring of a steel spring floating slab damping track. A wedge-shaped sliding block and an equal-strength beam form a conversion mechanism to transfer displacement to the deflection of the beam, and the deflection-induced strain is exerted on two FBGs. A special linear guide rail-slider and a precision rolling bearing have been adopted onto the conversion mechanism, which turned sliding friction into rolling friction and thus significantly reduced the friction during frequent alternating displacement measuring. Sensing principle and the corresponding theoretical derivation have been demonstrated. Experiment results show that the sensor has a sensitivity of 34.32 pm/mm and a high resolution of 0.0029 mm within a measurement range of 0~90 mm. Besides, the sensor has also a good measurement capability for micro-displacement within a range of 0~3 mm. The repeatability error and hysteresis error are 1.416% and 0.323%, respectively. Good creep resistance and high abrasion resistance for alternating displacement measurement have also been presented by a performance test. These excellent performances satisfy the requirements of high precision and long-term stability in structural health monitoring for machinery equipment and civil engineering, especially in the displacement monitoring of a floating slab damping track.

A non-contact fiber Bragg grating vibration sensor.

A non-contact vibration sensor based on fiber Bragg grating (FBG) sensing has been proposed and studied in this paper. The principle of the sensor as well as simulation and experimental analyses are introduced. When the distance between the movable head and the measured shaft changed, the diaphragm deformed under magnetic coupling of the permanent magnet on the measured magnetic shaft. As a result, the center wavelength of the FBG connected to the diaphragm changed, based on which the vibration displacement of the rotating shaft could be obtained. Experimental results show that the resonant frequency of the sensor is about 1500 Hz and the working band ranges within 0-1300 Hz, which is consistent with the simulation analysis result; the sensitivity is -1.694 pm/µm and the linearity is 2.92% within a range of 2-2.4 mm. It can be used to conduct non-contact measurement on the vibration of the rotating shaft system.

Effects of osmotic force and torque on microtubule bundling and pattern formation.

We report effects of polyethylene glycol (PEG, molecular weight of 35 kDa ) on microtubule (MT) bundling and pattern formation. Without PEG, polymerizing tubulin solutions of a few mg/ml that are initially subjected to a field that aligns MTs can spontaneously form striated birefringence patterns. These patterns form through MT alignment, bundling, and coordinated bundle buckling. With increasing PEG concentrations, solutions form progressively weaker patterns. At a sufficiently high PEG concentration ( approximately 0.5% by weight), the samples maintain a nearly uniform birefringence (i.e., no pattern) and laterally contract at a later stage. Concomitantly, on a microscopic level, the network of dispersed MTs that accompany the bundles in pure solutions disappear and the bundles become more distinct. We attribute the weakening of the pattern to the loss of the dispersed MT network, which is required to mediate the coordination of bundle buckling. We propose that the loss of the dispersed network and the enhanced bundling result from PEG associated osmotic forces that drive MTs together and osmotic torques that facilitate their bundling. Similarly, we attribute the lateral contraction of the samples to osmotic torques that tend to align crossing bundles in the network.

Polymerization force driven buckling of microtubule bundles determines the wavelength of patterns formed in tubulin solutions.

We present a model for the spontaneous formation of a striated pattern in polymerizing microtubule solutions. It describes the buckling of a single microtubule (MT) bundle within an elastic network formed by other similarly aligned and buckling bundles and unaligned MTs. Phase contrast and polarization microscopy studies of the temporal evolution of the pattern imply that the polymerization of MTs within the bundles creates the driving compressional force. Using the measured rate of buckling, the established MT force-velocity curve and the pattern wavelength, we obtain reasonable estimates for the MT bundle bending rigidity and the elastic constant of the network. The analysis implies that the bundles buckle as solid rods.

Microtubule bundling and nested buckling drive stripe formation in polymerizing tubulin solutions.

Various mechanisms govern pattern formation in chemical and biological reaction systems, giving rise to structures with distinct morphologies and physical properties. The self-organization of polymerizing microtubules (MTs) is of particular interest because of its implications for biological function. We report a study of the microscopic structure and properties of the striped patterns that spontaneously form in polymerizing tubulin solutions and propose a mechanism driving this assembly. Microscopic observations reveal that the pattern comprises wave-like MT bundles. The retardance of the solution and the fluorescence intensity of labeled MTs vary periodically in space, suggesting a coincident periodic variation in MT alignment and density. This wave-like structure forms through the development and coordinated buckling of initially aligned MT bundles. Both static magnetic fields and convective flow can induce the initial alignment. The nesting of the buckled MT bundles gives rise to density variations that are in quantitative accord with the data. We further propose that the buckling wavelength is selected by a balance between the bending energy of the bundles and the elastic energy of the MT network surrounding them. These studies reveal a unique physical chemical mechanism by which mechanical buckling couples with protein polymerization to produce macroscopic patterns. Self-organization of this type may be important to the formation of certain biological structures.