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Peaches are an ancient fruit in China, with great nutritional and commercial value. Peach fruit is a typical respiratory climacteric fruit, which is prone to browning within a short period of time after harvesting, and rapid browning and high browning degree occur during peach processing, which are difficult to control, affecting the quality and economic value of the fruit. At present, systematic research on the characteristics and mechanism of peach browning is lacking, as well as effective control techniques and methods. In this paper, the current status of research on the characteristics and mechanism of and the key factors for enzymatic browning in peach fruit is reviewed, and the techniques used for its control are summarized, aiming to provide a reference for the regulation of enzymatic browning during peach storage and processing and consequently to promote the quality improvement of fresh and processed peach products.

Simple Summary: Drugs work by binding to a specific 3D structure on a protein. Drug discovery has historically been driven by prior knowledge of function, either of a protein or chemical. This knowledge of function then drives investigations to probe chemical/protein interactions. We undertook a different approach. We first identified unique 3D structures, agnostic of function, and investigated whether they could lead us to innovative therapeutics. Using a synchrotron-based X-ray source, we first determined high-resolution structures of hundreds of proteins. With a supercomputer running analytical programs created by us, we identified novel 3D structures and screened for chemicals binding them. We then tested their ability to inhibit cancer growth without damaging normal cells. We identified a potent inhibitor of a deadly cancer, melanoma. It was not toxic to normal cells even at 2100-fold higher doses. It worked by inducing anoikis, a fundamental process of known importance for cancer. Therapeutics that selectively induce anoikis are needed. In summary, we demonstrate the power of using a 3D protein structure as the starting point to discover new biology and drugs. Drug discovery historically starts with an established function, either that of compounds or proteins. This can hamper discovery of novel therapeutics. As structure determines function, we hypothesized that unique 3D protein structures constitute primary data that can inform novel discovery. Using a computationally intensive physics-based analytical platform operating at supercomputing speeds, we probed a high-resolution protein X-ray crystallographic library developed by us. For each of the eight identified novel 3D structures, we analyzed binding of sixty million compounds. Top-ranking compounds were acquired and screened for efficacy against breast, prostate, colon, or lung cancer, and for toxicity on normal human bone marrow stem cells, both using eight-day colony formation assays. Effective and non-toxic compounds segregated to two pockets. One compound, Dxr2-017, exhibited selective anti-melanoma activity in the NCI-60 cell line screen. In eight-day assays, Dxr2-017 had an IC50 of 12 nM against melanoma cells, while concentrations over 2100-fold higher had minimal stem cell toxicity. Dxr2-017 induced anoikis, a unique form of programmed cell death in need of targeted therapeutics. Our findings demonstrate proof-of-concept that protein structures represent high-value primary data to support the discovery of novel acting therapeutics. This approach is widely applicable. [ABSTRACT FROM AUTHOR]

Targeting the dynamic image-motion problem of aerial cameras in the process of swing imaging, the image-motion compensation technology of aerial cameras based on the multi-dimensional motion of the secondary mirror was adopted. The secondary mirror was used as the image-motion compensation element, and the comprehensive image-motion compensation of the aerial camera was realized through the multi-dimensional motion of the secondary mirror. However, in the process of compensating for the image motion, the secondary mirror would be eccentric and inclined, which would cause the secondary mirror to be off-axis and affect the image quality. Therefore, a misalignment optical system model was established to study the relationship between the deviation vector and the misalignment of the secondary mirror, and the influence of the secondary mirror's motion on the distribution of the aberration was analyzed. In order to verify the image-motion compensation ability of the multi-dimensional motion of the secondary mirror, an experimental platform was built to conduct a laboratory imaging experiment and flight experiment on the aerial camera. The experimental results showed that the dynamic resolution of the aerial camera using the image-motion compensation technology could reach 74 lp/mm, and the image-motion compensation accuracy was better than 0.5 pixels, which met the design expectation. In conclusion, the image-motion compensation technology is expected to be applied to various high-precision optical imaging as well as optical detection systems. [ABSTRACT FROM AUTHOR]

In the athermal and apochromatic design of optical systems, the distribution of lens' optical powers and the selection of optical glass and structural materials are crucial. In this paper, an athermal and apochromatic design method is proposed for optical systems with a long focal length, large relative aperture, and wide spectrum. Firstly, a complex optical system composed of multiple lenses is equivalent to a two-component, single-lens system consisting of a replacement and an equivalent lens group. The optical glass for the replacement lens group is selected based on weight and the principle of material replacement in the 3D glass diagram, thus achieving an athermal and apochromatic design. Secondly, an athermal and apochromatic optical system with a focal length of 130 mm, an F-number of 2.0, a spectral range of 480 nm~800 nm, a field of view angle of 22°, and an operating temperature of −40 °C~+60 °C is designed. The modulation transfer function (MTF) at each field of view is greater than 0.6 at 50 lp/mm in the −40 °C~+60 °C temperature range, and the secondary spectrum aberration is 0.0056 mm, which is within the focal depth range of the optical system. [ABSTRACT FROM AUTHOR]

Given the impressive achievement of convolutional neural networks (CNNs) in grasping image priors from extensive datasets, they have been widely utilized for tasks related to image restoration. Recently, there is been significant progress in another category of neural architectures—Transformers. These models have demonstrated remarkable performance in natural language tasks and higher‐level vision applications. Despite their ability to address some of CNNs limitations, such as restricted receptive fields and adaptability issues, Transformer models often face difficulties when processing images with a high level of detail. This is because the complexity of the computations required increases significantly with the image's spatial resolution. As a result, their application to most high‐resolution image restoration tasks becomes impractical. In our research, we introduce a novel Transformer model, named DehFormer, by implementing specific design modifications in its fundamental components, for example, the multi‐head attention and feed‐forward network. Specifically, the proposed architecture consists of the three modules, that is, (a) multi‐scale feature aggregation network (MSFAN), (b) the gated‐Dconv feed‐forward network (GFFN), (c) and the multi‐Dconv head transposed attention (MDHTA). For the MDHTA module, our objective is to scrutinize the mechanics of scaled dot‐product attention through the utilization of per‐element product operations, thereby bypassing the need for matrix multiplications and operating directly in the frequency domain for enhanced efficiency. For the GFFN module, which enables only the relevant and valuable information to advance through the network hierarchy, thereby enhancing the efficiency of information flow within the model. Extensive experiments are conducted on the SateHazelk, RS‐Haze, and RSID datasets, resulting in performance that significantly exceeds that of existing methods. [ABSTRACT FROM AUTHOR]

For the purpose of achieving long-range, high-resolution, and ultra-wide-swath airborne earth imaging at extremely low-light levels (0.01 Lux), a low-light imaging system built on multi-detector optical butting was researched. Having decomposed the system's specifications and verified its low-light imaging capability, we proposed to employ an optical system with a large relative aperture and low distortion and achieve imaging through the field-of-view (FOV) butting facilitated by eight 1080P high-sensitivity scientific complementary metal-oxide semiconductor (SCMOS) detectors. This paper elaborates on the design concept of the mechanical configuration of the imaging system; studies the calculation method of the structural parameters of the reflection prism; provides mathematical expressions for geometric parameters, such as the length and width of the splicing prism; and designs in detail the splicing structure of six reflection prisms for eight-channel beam splitting. Based on the design and computational results, a high-resolution, wide-swath imaging system for an ambient illuminance of 0.01 Lux was developed. Exhibiting a ground sampling distance (GSD) of 0.5 m (at a flight height of 5 km), this low-light imaging system keeps the FOV overlap ratio between adjacent detectors below 3% and boasts an effective image resolution of 4222 × 3782. The results from flight testing revealed that the proposed imaging system is capable of generating wide-swath, high-contrast resolution imagery under airborne and low-light conditions. As such, the way the system is prepared can serve as a reference point for the development of airborne low-light imaging devices. [ABSTRACT FROM AUTHOR]

Leveraging space-based optical platforms for space debris and defunct spacecraft detection presents several advantages, including a wide detection range, immunity to cloud cover, and the ability to maintain continuous surveillance on space targets. As a result, it has become an essential approach for accomplishing tasks related to space situational awareness. However, the prediction of the orbits of space objects is crucial for the success of such missions, and current technologies face challenges related to accuracy, reliability, and practical efficiency. These challenges limit the performance of space-based optical space situational awareness systems. To drive progress in this field and establish a more effective and reliable space situational awareness system based on space optical platforms, this paper conducts a retrospective overview of research advancements in this area. It explores the research landscape of orbit determination methods, encompassing orbit association methods, initial orbit determination methods, and precise orbit determination methods, providing insights from international perspectives. The article concludes by highlighting key research areas, challenges, and future trends in current space situational awareness systems and orbit determination methods. [ABSTRACT FROM AUTHOR]

There is a growing need for the lightweight acquisition, tracking, and pointing (APT) system during satellite launches due to the escalating demand in space missions. The APT system may work under multiple loading cases during different launch steps. Hence, this study introduces an innovative amalgamation of genetic operation and bi-directional evolutionary structural optimization (BESO) to fulfill the multi-objective requirements through the attainment of Pareto optimal fronts. A typical instance in two dimensions illustrates the effectiveness of the innovative multi-objective approach by contrasting the outcomes acquired from a solitary fulfillment requirement under two distinct burdens. Furthermore, the novel multi-objective method is utilized to remove inefficient material from the APT system by 20.12%. To ensure the safety of the lightweight design, the simulation and experiment of random vibration are both investigated according to the fundamental natural frequency of the launcher. [ABSTRACT FROM AUTHOR]

The purpose of dark image enhancement is to restore dark images to visual images under normal lighting conditions. Due to the ill-posedness of the enhancement process, previous enhancement algorithms often have overexposure, underexposure, noise increases and artifacts when dealing with complex and changeable images, and the robustness is poor. This article proposes a new enhancement approach consisting in constructing a dim light enhancement network with more robustness and rich detail features through the collaborative constraint of multiple self-coding priors (CCMP). Specifically, our model consists of two prior modules and an enhancement module. The former learns the feature distribution of the dark light image under normal exposure as an a priori term of the enhancement process through multiple specific autoencoders, implicitly measures the enhancement quality and drives the network to approach the truth value. The latter fits the curve mapping of the enhancement process as a fidelity term to restore global illumination and local details. Through experiments, we concluded that the new method proposed in this article can achieve more excellent quantitative and qualitative results, improve detail contrast, reduce artifacts and noise, and is suitable for dark light enhancement in multiple scenes. [ABSTRACT FROM AUTHOR]

High-precision images enable electrical capacitance tomography (ECT) to obtain more reliable measurement results, meaning that the reconstruction algorithm is particularly important. Some excellent numerical algorithms have successfully solved the inverse problem for ECT imaging, but their imaging quality is relatively low. To solve this problem, this paper proposes a new reconstruction algorithm based on regularized extreme learning machines (RELMs). The implementation of the algorithm is mainly divided into two steps: (1) according to a large number of training samples, the RELM model can be obtained by the iterative split Bregman (ISB) algorithm, which can describe the mapping relationship between the capacitance correlation coefficient and the imaging target well, and (2) the capacitance correlation coefficient is calculated, which is then used as input to the RELM model to predict the final imaging. Both simulation and experimental results show that the RELM algorithm achieves greater improvement in imaging quality and robustness, and provides new development ideas for the ECT. [ABSTRACT FROM AUTHOR]

The infrared search and track system (IRST) is a type of special electrical optical (EO) system that can be used in various scenarios to fulfill situation awareness, reconnaissance, and tracking of targets. We proposed a homogeneous coordinate transformation method to analyze the residual image wandering induced by the rotation of the scanning platform and the compensation fast steering mirror and help with the commonly trivial selection of the telescope magnification and the objective focal length. The analysis and simulation are carried out with specified IRST optics, which adopt a 640 × 512 array and 15 μm pitch detector, in a focal range of 60 mm~360 mm, and a scan speed of 360°/s to 60 °/s at 50 fps, and optical specifications are determined further. The presented optical system, with only three kinds of common infrared materials, works at 3.7 μm~4.8 μm, demonstrates good image performance and tolerance characteristics, and shows potential in manufacturing. Also, the resulting image wandering of 8 μm, less than a 0.6-pixel size, at an integral time of 16 ms, proves the correctness of the method and makes the scheme of considerable interest for electrical optical systems. [ABSTRACT FROM AUTHOR]

The wide-field imaging system carried on a high-altitude or near-space vehicle takes high-resolution images of the ground to measure and map targets. With the improvement of imaging resolution and measurement accuracy, the focal length of the wide-field imaging system is getting longer. The requirement for image motion compensation (IMC) accuracy is getting higher, and the influence of optical path coupling is increasing within the process of two-dimensional (2D) IMC. To further improve the IMC accuracy of the wide-field imaging system, an innovative IMC method is first proposed in this paper. The method is based on the 2D motion of the scanning platform and secondary mirror. Secondly, to solve the optical coupling problem in the process of 2D IMC, the coupling phenomenon is analyzed. The coupling relationships between 2D scanning motion, 2D secondary mirror motion and image motion is derived from the compensation process. A complete 2D IMC model is established, and a 2D IMC method, including an optical path decoupling correct regulator (ODCR), is designed. Finally, the method is verified in laboratory and field flight tests. The results show that the proposed method can effectively correct the coupling error of the optical path in the process of IMC and achieve high-resolution 2D IMC. When the scanning speed is 60°/s and the exposure time is 2 ms, the accuracy of the 2D IMC is up to 0.57pixels (RMS) in the pitch direction, and 0.46 pixels (RMS) in the roll direction. [ABSTRACT FROM AUTHOR]

The previous study has researched that combining YKL-5-124, CDK7 specific target drug with anti-PD-1 treatment had a survival advantage in various Small Cell Lung Cancer models. However, the molecular mechanism that YKL-5-124 triggers inflammatory response remains unknown. This study investigates the effects of CDK7 inhibition by YKL-5-124 on two DNA damage pathways (ATM and ATR) of SCLC in vitro. The result of this study will reveal the effects of CDK7 inhibition by YKL-5-124 on the molecular mechanisms of SCLC and potentially promote the development of new anticancer treatment strategies based on immunity manipulation.

The combination of single-pixel imaging and single photon-counting technology enables ultra-high-sensitivity photon-counting imaging. In order to shorten the reconstruction time of single-photon counting, the algorithm of compressed sensing is used to reconstruct the underdetermined image. Compressed sensing theory based on prior constraints provides a solution that can achieve stable and high-quality reconstruction, while the prior information generated by the network may overfit the feature extraction and increase the burden of the system. In this paper, we propose a novel sparse autoencoder network prior for the reconstruction of the single-pixel imaging, and we also propose the idea of multi-channel prior, using the fully connected layer to construct the sparse autoencoder network. Then, take the network training results as prior information and use the numerical gradient descent method to solve underdetermined linear equations. The experimental results indicate that this sparse autoencoder network prior for the single-photon counting compressed images reconstruction has the ability to outperform the traditional one-norm prior, effectively improving the reconstruction quality. [ABSTRACT FROM AUTHOR]

In order to capture true-color information of distant targets under extremely low light, a large-format low-light imaging system is designed based on an RGB filter wheel. By decomposing the system indicators, this study proposes a method for acquiring low-light true-color images using a large-aperture, low-distortion optical lens combined with an RGB filter wheel capable of multi-line sequential exposure. The optical field segmentation is achieved using a four-panel optical reflective prism, and the images from four high-sensitivity SCOMS detectors are stitched together to form a composite image. The working principle of the system is explained, and the low-light imaging capability is thoroughly evaluated. The dimensions and rotation speed of the filter wheel are then calculated in detail, ensuring accurate synchronization of the filter wheel's speed and exposure time. The calculation method for the parameters of the four-panel reflective prism structure is investigated, mathematical expressions for the geometric parameters of the prism assembly are provided, and a prism assembly suitable for four-way spectral separation is designed. Based on the research and design results, a large-swath-width, low-light true-color imaging system is developed that is suitable for an environmental illuminance of 0.01 lux. The system achieves a ground pixel resolution of 0.5 m (at an altitude of 5 km) and an effective image resolution of 4 K × 4 K, and is capable of accurately reproducing target color information. Laboratory and field flight tests verified that the large-swath-width images obtained by the imaging system are clear, with high contrast and resolution. After image fusion and spectral registration, the color images exhibit full saturation and high fidelity, meeting the requirements of low-light true-color imaging under airborne conditions. The design methodology of this low-light imaging system can serve as a reference for the development of airborne low-light imaging equipment. [ABSTRACT FROM AUTHOR]

The objects in remote sensing images are normally densely packed, arbitrarily oriented, and surrounded by complex backgrounds. Great efforts have been devoted to developing oriented object detection models to accommodate such data characteristics. We argue that an effective detection model hinges on three aspects: feature enhancement, feature decoupling for classification and localization, and an appropriate bounding box regression scheme. In this article, we instantiate the three aspects on top of the classical Faster R-CNN, with three novel components proposed. First, we propose a weighted fusion and refinement (WFR) module, which adaptively weighs multi-level features and leverages the attention mechanism to refine the fused features. Second, we decouple the RoI (region of interest) features for the subsequent classification and localization via a lightweight affine transformation-based feature decoupling (ATFD) module. Third, we propose a post-classification regression (PCR) module for generating the desired quadrilateral bounding boxes. Specifically, PCR predicts the precise vertex location on each side of a predicted horizontal box, by simply learning the following: (i) classify the discretized regression range of the vertex, and (ii) revise the vertex location with an offset. We conduct extensive experiments on the DOTA, DIOR-R, and HRSC2016 datasets to evaluate our method. [ABSTRACT FROM AUTHOR]

The use of airborne-mapping technology plays a key role in the acquisition of large-scale basic geographic data information, especially in various important civil/military-mapping missions. However, most airborne-mapping cameras are limited by parameters, such as the flight altitude, working-environment temperature, and so on. To solve this problem, in this paper, we designed a panchromatic wide-spectrum optical system with a focusing function. Based on the catadioptric optical structure, the optical system approached a telecentric optical structure. Sharp images at different object distances could be acquired by micro-moving the focusing lens. At the same time, an optical passive compensation method was adopted to realize an athermalization design in the range of −40–60 °C. According to the design parameters of the optical system, we analyzed the influence of system focusing on mapping accuracy during the focusing process of the airborne-mapping camera. In the laboratory, the camera calibration and imaging experiments were performed at different focusing positions. The results show that the experimental data are consistent with the analysis results. Due to the limited experiment conditions, only a single flight experiment was performed. The results show that the airborne-mapping camera can achieve 1:5000 scale-imaging accuracy. Flight experiments for different flight altitudes are being planned, and the relevant experimental data will be released in the future. In conclusion, the airborne-mapping camera is expected to be applied in various high-precision scale-mapping fields. [ABSTRACT FROM AUTHOR]

In current years, natural pigments are facing a fast-growing global market due to the increase of people's awareness of health and the discovery of novel pharmacological effects of various natural pigments, e.g., carotenoids, flavonoids, and curcuminoids. However, the traditional production approaches are source-dependent and generally subject to the low contents of target pigment compounds. In order to scale-up industrial production, many efforts have been devoted to increasing pigment production from natural producers, via development of both in vitro plant cell/tissue culture systems, as well as optimization of microbial cultivation approaches. Moreover, synthetic biology has opened the door for heterologous biosynthesis of pigments via design and re-construction of novel biological modules as well as biological systems in bio-platforms. In this review, the innovative methods and strategies for optimization and engineering of both native and heterologous producers of natural pigments are comprehensively summarized. Current progress in the production of several representative high-value natural pigments is also presented; and the remaining challenges and future perspectives are discussed. [ABSTRACT FROM AUTHOR]

This paper gives a class of multilinear uncertain polynomials to which the Edge Theorem is applicable. In the paper, a notion of "symmetric uncertainty structure" is introduced. The main result is as follows: If a multilinear uncertain polynomial has a symmetric uncertainty structure and the uncertain parameters are nonoverlapping, then the corresponding value sets will be convex polygons. This means that the use of the zero exclusion condition to test the robust stability of such uncertain polynomials is feasible since we need only to calculate the extreme points of the convex polygons. Furthermore, a version of the Edge Theorem can be used to test the robust stability of such uncertain polynomials.

A compact planar composite antenna with dual‐band performance and good unidirectional radiation is proposed for handheld radio frequency identification reader application. The novelty of the proposed antenna is that it adopts the combination of planar Moxon and quasi‐Yagi interleaved structures. The Moxon structure due to its compact size is designed to operate in the lower band, while the quasi‐Yagi structure with the shared area is designed for the higher band. The lower and higher frequency bands of the antenna can be designed independently. Detailed design ideas and experimental results are presented. Measured results show that the fabricated antenna has a moderate gain of better than 5 dB and a large front‐to‐back ratio of more than 15 dB in both ultrahigh frequency 902‐928 MHz and industrial scientific and medical 2.4‐2.4835 GHz bands with low cross‐polarization levels. The antenna has the advantages of simple structure, easy processing, and excellent performance in terms of impedance matching and radiation patterns. It can be easily adjusted for other wireless applications, where both end‐fire radiation and dual‐band operation are required. [ABSTRACT FROM AUTHOR]

Ring extensions are a well-studied topic in ring theory. In this paper, we study the structure of the Gauss extension of a Galois ring. We determine the structures of the extension ring and its unit group. [ABSTRACT FROM AUTHOR]

To determine the feasibility of microalgae-yeast mixed culture using the liquid digestate of dairy wastewater (LDDW) for biofuels and single cell protein (SCP) production, the cell growth, nutrient removal and outputs evaluation of the mono and mixed culture of Chlorella vulgaris and Yarrowia lipolytica in LDDW were investigated by adding glycerol as carbon source. The results showed that the mixed culture could enhance the biological utilization efficiency of nitrogen and phosphorus, and obtain higher yield of biomass (1.62 g/L), lipid (0.31 g/L), protein (0.51 g/L), and higher heating value (34.06 KJ/L). Compared with the mono culture of C. vulgaris , a decline of the transcription level in nitrate reductase and glutamine synthetase II genes in C. vulgaris was observed in the mixed culture when ammonia was sufficient. The results suggest the possibility of using the mixed culture for the efficient treatment of LDDW and resources recycling. [ABSTRACT FROM AUTHOR]