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The goal of the multi-focus image fusion (MFIF) task is to merge images with different focus areas into a single clear image. In real world scenarios, in addition to varying focus attributes, there are also exposure differences between multi-source images, which is an important but often overlooked issue. To address this drawback and improve the development of the MFIF task, a new image fusion dataset is introduced called EDMF. Compared with the existing public MFIF datasets, it contains more images with exposure differences, which is more challenging and has a numerical advantage. Specifically, EDMF contains 1000 pairs of color images captured in real-world scenes, with some pairs exhibiting significant exposure difference. These images are captured using smartphones, encompassing diverse scenes and lighting conditions. Additionally, in this paper, a baseline method is also proposed, which is an improved version of memory unit-based unsupervised learning. By incorporating multiple adaptive memory units and spatial frequency information, the network is guided to focus on learning features from in-focus areas. This approach enables the network to effectively learn focus features during training, resulting in clear fused images that align with human visual perception. Experimental results demonstrate the effectiveness of the proposed method in handling exposure difference, achieving excellent fusion results in various complex scenes. [ABSTRACT FROM AUTHOR]

The main disadvantage of the electromagnetic acoustic transducer (EMAT) is low energy-conversion efficiency and low signal-to-noise ratio (SNR). This problem can be improved by pulse compression technology in the time domain. In this paper, a new coil structure with unequal spacing was proposed for a Rayleigh wave EMAT (RW-EMAT) to replace the conventional meander line coil with equal spacing, which allows the signal to be compressed in the spatial domain. Linear and nonlinear wavelength modulations were analyzed to design the unequal spacing coil. Based on this, the performance of the new coil structure was analyzed by the autocorrelation function. Finite element simulation and experiments proved the feasibility of the spatial pulse compression coil. The experimental results show that the received signal amplitude is increased by 2.3~2.6 times, the signal with a width of 20 μs could be compressed into a δ-like pulse of less than 0.25 μs and the SNR is increased by 7.1–10.1 dB. These indicate that the proposed new RW-EMAT can effectively enhance the strength, time resolution and SNR of the received signal. [ABSTRACT FROM AUTHOR]

Soil salinity constrains agricultural development in arid regions. Flax is an economically important crop in many countries, and screening or breeding salinity-resistant flax cultivars is necessary. Based on the previous screening of flaxseed cultivars C71 (salt-sensitive) and C116 (salt-tolerant) as test materials, flax seedlings stressed with different concentrations of NaCl (0, 100, 150, 200, and 250 mmol/L) for 21 days were used to investigate the effects of salt stress on the growth characteristics, osmotic regulators, and antioxidant capacity of these flax seedlings and to reveal the adaptive responses of flax seedlings to salt stress. The results showed that plant height and root length of flax were inhibited, with C116 showing lower growth than C71. The concentrations of osmotic adjustment substances such as soluble sugars, soluble proteins, and proline were higher in the resistant material, C116, than in the sensitive material, C71, under different concentrations of salt stress. Consistently, C116 showed a better rapid scavenging ability for reactive oxygen species (ROS) and maintained higher activities of antioxidant enzymes to balance salt injury stress by inhibiting growth under salt stress. A transcriptome analysis of flax revealed that genes related to defense and senescence were significantly upregulated, and genes related to the growth and development processes were significantly downregulated under salt stress. Our results indicated that one of the important adaptations to tolerance to high salt stress is complex physiological remediation by rapidly promoting transcriptional regulation in flax. [ABSTRACT FROM AUTHOR]

Tracking aircraft and parachutes plays a vital role in airdrop experiments. It is necessary to study a parachute's open state and flight trajectory. More scholars are looking into how to efficiently and accurately obtain parachute deformation data and trajectory data. At present, the actual data collection primarily involves experimenters holding high-definition high-speed cameras to track and shoot parachutes to obtain the image sequences of the parachutes during the airdrop process. However, these methods cannot obtain the trajectories of the parachutes and they are susceptible to interference from human factors. In this paper, we designed TuSeSy, an intelligent turntable servo system that can track the aircraft and parachutes in airdrop tests automatically. Specifically, TuSeSy generates the control commands according to the differences between the actual taken images and the inferred images by tracking algorithms (so as to actually track the target). In addition, we propose an effective multi-target tracking switch algorithm based on the image frame difference and optical flow, to achieve real-time switching from the aircraft to the parachute in an airdrop test. To evaluate the performance of TuSeSy, we conducted extensive experiments; the experimental results show that TuSeSy not only solves the problem of wrong target tracking, but it also reduces computational overhead. Moreover, the multi-target tracking switch algorithm has higher computing efficiency and reliability compared to other tracking switch approaches, ensuring the practical applications of the turntable servo system. [ABSTRACT FROM AUTHOR]

Object detection has attracted great attention in recent years. Many experts and scholars have proposed efficient solutions to address object detection problems and achieve perfect performance. For example, coordinate-based anchor-free (CBAF) module was proposed recently to predict the category and the adjustments to the box of the object by its feature part and its contextual part features, which are based on feature maps divided by spatial coordinates. However, these methods do not work very well for some particular situations (e.g., small object detection, scale variation, deformations, etc.), and the accuracy of object detection still needs to be improved. In this paper, to address these problems, we proposed ODEM-GAN based on CBAF, which utilizes generative adversarial networks to implement the detection of a deformed object. Specifically, ODEM-GAN first generates the object deformation features and then uses these features to enhance the learning ability of CBFA for improving the robustness of the detection. We also conducted extensive experiments to validate the effectiveness of ODEM-GAN in the simulation of a parachute opening process. The experimental results demonstrate that, with the assistance of ODEM-GAN, the AP score of CBAF for parachute detection is 88.4%, thereby the accuracy of detecting the deformed object by CBAF significantly increases. [ABSTRACT FROM AUTHOR]

Traditional video object segmentation often has low detection speed and inaccurate results due to the jitter caused by the pan-and-tilt or hand-held devices. Deep neural network (DNN) has been widely adopted to address these problems; however, it relies on a large number of annotated data and high-performance computing units. Therefore, DNN is not suitable for some special scenarios (e.g., no prior knowledge or powerful computing ability). In this paper, we propose RoiSeg, an effective moving object segmentation approach based on Region-of-Interest (ROI), which utilizes unsupervised learning method to achieve automatic segmentation of moving objects. Specifically, we first hypothesize that the central n × n pixels of images act as the ROI to represent the features of the segmented moving object. Second, we pool the ROI to a central point of the foreground to simplify the segmentation problem into a classification problem based on ROI. Third but not the least, we implement a trajectory-based classifier and an online updating mechanism to address the classification problem and the compensation of class imbalance, respectively. We conduct extensive experiments to evaluate the performance of RoiSeg and the experimental results demonstrate that RoiSeg is more accurate and faster compared with other segmentation algorithms. Moreover, RoiSeg not only effectively handles ambient lighting changes, fog, salt and pepper noise, but also has a good ability to deal with camera jitter and windy scenes. [ABSTRACT FROM AUTHOR]

Si single crystal was implanted with 230 keV He+ ions to a fluence of 5 × 1016/cm2 at 600 °C. The structural defects in Si implanted with He at 600 °C and then annealed at 1000 °C were investigated by transmission electron microscopy (TEM) and high-resolution transmission electron microscopy (HRTEM). The microstructure of an as-implanted sample is provided for comparison. After annealing, rod-like defects were diminished, while tangled dislocations and large dislocation loops appeared. Dislocation lines trapped by cavities were directly observed. The cavities remained stable except for a transition of shape, from octahedron to tetrakaidecahedron. Stacking-fault tetrahedrons were found simultaneously. Cavity growth was independent of dislocations. The evolution of observed lattice defects is discussed. [ABSTRACT FROM AUTHOR]

Aerogels are one of the most interesting materials of the 21st century owing to their high porosity, low density, and large available surface area. Historically, aerogels have been used for highly efficient insulation and niche applications, such as interstellar particle capture. Recently, aerogels have made their way into the composite universe. By coupling nanomaterial with a variety of matrix materials, lightweight, high-performance composite aerogels have been developed for applications ranging from lithium-ion batteries to tissue engineering materials. In this paper, the current status of aerogel composites based on nanomaterials is reviewed and their application in environmental remediation, energy storage, controlled drug delivery, tissue engineering, and biosensing are discussed. [ABSTRACT FROM AUTHOR]

LaFeO3 nanoparticle-modified TiO2 nanotube arrays were fabricated through facile hydrothermal growth. The absorption edge of LaFeO3 nanoparticle-modified TiO2 nanotube arrays displaying a red shift to ~540 nm was indicated by the results of diffuse reflectance spectroscopy (DRS) when compared to TiO2 nanotube arrays, which means that the sample of LaFeO3 nanoparticle-modified TiO2 nanotube arrays had enhanced visible light response. Photoluminescence (PL) spectra showed that the LaFeO3 nanoparticle-modified TiO2 nanotube arrays efficiently separated the photoinduced electron–hole pairs and effectively prolonged the endurance of photogenerated carriers. The results of methylene blue (MB) degeneration under simulated visible light illumination showed that the photocatalytic activity of LaFeO3 nanoparticle-modified TiO2 nanotube arrays is obviously increased. LaFeO3 nanoparticle-modified TiO2 nanotube arrays with 12 h hydrothermal reaction time showed the highest degradation rate with a 2-fold enhancement compared with that of pristine TiO2 nanotube arrays. [ABSTRACT FROM AUTHOR]