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Hyaluronan is widely used in cosmetics and pharmaceutics. Development of robust and safe cell factories and cultivation approaches to efficiently produce hyaluronan is of many interests. Here, we describe the metabolic engineering of Corynebacterium glutamicum and application of a fermentation strategy to manufacture hyaluronan with different molecular weights. C. glutamicum is engineered by combinatorial overexpression of type I hyaluronan synthase, enzymes of intermediate metabolic pathways and attenuation of extracellular polysaccharide biosynthesis. The engineered strain produces 34.2 g L −1 hyaluronan in fed-batch cultures. We find secreted hyaluronan encapsulates C. glutamicum , changes its cell morphology and inhibits metabolism. Disruption of the encapsulation with leech hyaluronidase restores metabolism and leads to hyper hyaluronan productions of 74.1 g L −1 . Meanwhile, the molecular weight of hyaluronan is also highly tunable. These results demonstrate combinatorial optimization of cell factories and the extracellular environment is efficacious and likely applicable for the production of other biopolymers. Bioproduction of hyaluronan needs increases in yield and greater diversity of the molecular weights. Here, the author increases hyaluronan production and diversifies the molecular weights through engineering the hyaluronan biosynthesis pathway and disruption of Corynebacterium glutamicum encapsulation caused by secreted hyaluronan.

High-yield biosynthesis of hyaluronan (HA) with controllable molecular weights (MWs) remains challenging due to the poorly understood function of Class I HA synthase (HAS) and the metabolic imbalance between HA biosynthesis and cellular growth. Here, we systematically characterize HAS to identify crucial regions involved in HA polymerization, secretion, and MW control. We construct HAS mutants that achieve complete HA secretion and expand the MW range from 300 to 1400 kDa. By dynamically regulating UDP-glucose 6-dehydrogenase activity and applying an adaptive evolution approach, we recover cell normal growth with increased metabolic capacities. Final titers and productivities for high MW HA (500 kDa) and low MW HA (10 kDa) reach 45 g L −1 and 105 g L −1 , 0.94 g L −1 h −1 and 1.46 g L −1 h −1 , respectively. Our findings advance our understanding of HAS function and the interplay between cell metabolism and morphology, and provide a shape-guided engineering strategy to optimize microbial cell factories. Biosynthesis of hyaluronan (HA) with controlled molecular weights is challenging due to the poorly understood function of the HA synthase (HAS). Here, the authors characterise and engineer HAS and conduct strain engineering to expand the molecular weight range and achieve high titres of both high and low molecular weight HA.

With the phasor measurement units (PMUs) being widely utilized in power systems, a large amount of data can be stored. If transient stability assessment (TSA) method based on the deep learning model is trained by this dataset, it requires high computation cost. Furthermore, the fact that unstable cases rarely occur would lead to an imbalanced dataset. Thus, power system transient stability status prediction has the bias problem caused by the imbalance of sample size and class importance. Faced with such a problem, a TSA model based on the sample selection method is proposed in this paper. Sample selection aims to optimize the training set to speed up the training process while improving the preference of the TSA model. The typical samples which can accurately express the spatial distribution of the raw dataset are selected by the proposed method. Primarily, based on the location of training samples in the feature space, the border samples are selected by trained support vector machine (SVM), and the edge samples are selected by the assistance of the approximated tangent hyperplane of a class surface. Then, the selected samples are input to stacked sparse autoencoder (SSAE) as the final classifier. Simulation results in the IEEE 39‐bus system and the realistic regional power system of Eastern China show the high performance of the proposed method.

Chondroitin sulfate (CS) has a wide range of physiological functions and clinical applications. However, the biosynthesis of chondroitin oligosaccharides (o-CHs) and sulfate derivatives with specific length is always challenging. Herein, we report enzymatic strategies for producing homogeneous o-CHs and its sulfate derivatives from microbial sourced chondroitin. Chondroitin disaccharides, tetrasaccharides, hexasaccharides, octasaccharides, and decasaccharides with defined structure were produced by controllably depolymerizing microbial sourced chondroitin with an engineered chondroitinase ABC I. The highest conversion rates of the above corresponding o-CHs were 65.5%, 32.1%, 12.7%, 7.2%, and 16.3%, respectively. A new efficient enzymatic sulfation system that directly initiates from adenosine 5′-triphosphate (ATP) and sulfate was developed and improved the sulfation of chondroitin from 8.3% to 85.8% by optimizing the temperature, sulfate and ATP concentration. o-CHs decasaccharide, octasaccharide, hexasaccharide, tetrasaccharide and disaccharide were modified and the corresponding sulfate derivatives with one sulfate group were prepared. The enzymatic approaches constructed here for preparing o-CHs and its sulfate derivatives pave the way for the study of structure-activity relationship and applications.

In the online fashion market, sellers often modify their product images by adding image frames or other non-native contents, or compositing different images, to emphasize the features of their products and get more attention. However, from the buyer’s point of view, these excessive contents are often redundant, interfering with the evaluation of the major contents or products in the image. Additionally, it makes it harder for product archiving in the fashion market. In this thesis, we will introduce several novel algorithms based on image processing techniques as well as deep learning to analyze and detect these added synthetic contents in the product images on a fashion market. Promising results have been shown through comprehensive evaluations on several testing datasets and comparisons to other deep learning models that have been used for similar purposes.The development of image quality assessment algorithms has been a very active research area in the field of image processing, and there have been numerous methods proposed. However, most of the existing methods focus on digital images that only or mainly contain pictures or photos taken by digital cameras. Traditional approaches evaluate an input image as a whole and try to estimate a quality score for the image, to give viewers an idea of how good or satisfying the image looks. In this thesis, we focus on the quality evaluation of elements such as texts, bar-codes, QR-codes, lines, and hand-writings in target images, which is often neglected in many other related works. Estimating a quality score for this kind of information can be based on whether or not it is readable by a human, or recognizable by a decoder. Moreover, we mainly study the viewing quality of the scanned document of a printed image. For this purpose, we propose a novel document image quality assessment (DIQA) algorithm that can determine the scanning resolution for a document or regions in a document that is optimized for cloud and host destinations. We also develop an automatic compression system for scanned document pages based on our optimal resolution algorithm, to achieve optimal file sizes for scanned documents without loss of key information. Experimental results on our testing images successfully demonstrate the effectiveness of our method.When it comes to the image signal processor (ISP) for digital cameras, denoising and tonemapping are two important steps in high-dynamic-range (HDR) imaging. Tone-mapping, which adjusts the brightness and contrast of a given image, can significantly amplify the noise, especially in low-light areas, posing challenges to denoising. Denoising, on the other hand, can undo the enhanced contrast from tone-mapping steps if not tuned accordingly, and many times assumes the linear inputs, which no longer holds due to the multi-exposure capture and non-linear tone-mapping operation. While such entanglement between tonemapping and denoising exists, the existing image processing unit (IPU) or image signal processor pipeline usually instantiates the two steps as separate and isolated modules, making the balancing of the two modules’ effects difficult. In this work, observing that both operations can benefit from multi-scale processing (i.e. decomposing an image into highor low-frequency components and performing denoising and tone-mapping accordingly), we propose a joint multi-scale denoising and tone-mapping framework with both operations in mind for HDR imaging. Our joint multi-scale DCT-based network is trained in an end-toend format that optimizes both operators together. On recent HDR benchmark datasets, we show both quantitatively and qualitatively that our proposed framework achieves better results than state-of-the-art HDR tone-mapping methods that separately perform denoising and tone-mapping procedures.

UDP-sugars, as active forms of monosaccharides, play integral roles in glycosylation and biosynthesis of polysaccharides. Although enzymatic catalysis has achieved great process, the comparatively low productivity and the time-consuming enzyme purification processes restricted its practical applications. Here, we developed two CipA-dependent enzyme immobilization systems for synthesis of UDP-GlcNAc and UDP-GlcA. Initially, we selected and identified the enzyme combinations of PpAmgK and SeGlmU for UDP-GlcNAc (3.19 mM) synthesis, and AtGlcAK and BlUSP for UDP-GlcA (1.83 mM) synthesis. After optimizing the molar ratios of substrates, the production of UDP-GlcNAc and UDP-GlcA increased to 17.33 mM and 9.03 mM when setting UTP:GlcNAc:ATP and UTP:GlcA:ATP as 1:1:1 and 1:2:1, respectively. Then, the polyphosphokinase SePPK for recycling ADP and PPi was introduced, resulting in a significant increase in UDP-GlcNAc (29.33 mM) and UDP-GlcA (20.87 mM). Eventually, the CipA-based immobilization systems were developed for repetitive catalysis. The combinations of PSK-(G 4 S) 3 -CipA and CipA-(G 4 S) 3 -ABK yielded the comparable productions of UDP-GlcNAc (28.66 mM, 17.40 g/L) and UDP-GlcA (20.34 mM, 11.80 g/L) within 75 min. This study presents a convenient and reusable CipA-based enzyme immobilization system for synthesis of UDP-sugars, showing great potential for enzymatic production of UDP-GlcNAc and UDP-GlcA.

An image processing unit (IPU), or image signal processor (ISP) for high dynamic range (HDR) imaging usually consists of demosaicing, white balancing, lens shading correction, color correction, denoising, and tone-mapping. Besides noise from the imaging sensors, almost every step in the ISP introduces or amplifies noise in different ways, and denoising operators are designed to reduce the noise from these sources. Designed for dynamic range compressing, tone-mapping operators in an ISP can significantly amplify the noise level, especially for images captured in low-light conditions, making denoising very difficult. Therefore, we propose a joint multi-scale denoising and tone-mapping framework that is designed with both operations in mind for HDR images. Our joint network is trained in an end-to-end format that optimizes both operators together, to prevent the tone-mapping operator from overwhelming the denoising operator. Our model outperforms existing HDR denoising and tone-mapping operators both quantitatively and qualitatively on most of our benchmarking datasets.

High-quality two-dimensional atomic layered p–n heterostructures are essential for high-performance integrated optoelectronics. The studies to date have been largely limited to exfoliated and restacked flakes, and the controlled growth of such heterostructures remains a significant challenge. Here we report the direct van der Waals epitaxial growth of large-scale WSe 2 /SnS 2 vertical bilayer p–n junctions on SiO 2 /Si substrates, with the lateral sizes reaching up to millimeter scale. Multi-electrode field-effect transistors have been integrated on a single heterostructure bilayer. Electrical transport measurements indicate that the field-effect transistors of the junction show an ultra-low off-state leakage current of 10 −14 A and a highest on–off ratio of up to 10 7 . Optoelectronic characterizations show prominent photoresponse, with a fast response time of 500 μs, faster than all the directly grown vertical 2D heterostructures. The direct growth of high-quality van der Waals junctions marks an important step toward high-performance integrated optoelectronic devices and systems. Growth of large area and defect-free two-dimensional semiconductor layers for high-performance p–n junction applications has been a great challenge. Yang et al. prepare millimeter-scaled WSe 2 /SnS 2 vertical heterojunctions by two-step van der Waals epitaxy, which show excellent optoelectronic properties.

Lateral heterostructures of two-dimensional transition metal dichalcogenides (TMDs) have offered great opportunities in the engineering of monolayer electronics, catalysis and optoelectronics. To explore the full potential of these materials, developing methods to precisely control the spatial scale of the heterostructure region is crucial. Here, we report the synthesis of ultra-long MoS 2 nano-channels with several micrometer length and 2–30 nanometer width within the MoSe 2 monolayers, based on intrinsic grain boundaries (GBs). First-principles calculations disclose that the strain fields near the GBs not only lead to the preferred substitution of selenium by sulfur but also drive coherent extension of the MoS 2 channel from the GBs. Such a strain-driven synthesis mechanism is further shown applicable to other topological defects. We also demonstrate that the spontaneous strain of MoS 2 nano-channels can further improve the hydrogen production activity of GBs, paving the way for designing GB based high-efficient TMDs in the catalytic application. Controlled growth of heterostructures within 10 nm scale is crucial for potential applications of transition metal dichalcogenides. Here, the authors report strain-driven synthesis of ultra-long MoS 2 nano-channels having several micrometers length and 2–30 nm width embedded within MoSe 2 monolayer.

This study investigates the mechanical, thermal, and water absorption properties of high-density polyethylene (HDPE) composites filled with barley straw and varying amounts of waste rubber. The research aims to develop sustainable materials that repurpose agricultural and industrial waste while addressing resource scarcity and waste management challenges. Composites were prepared using a twin-rotor mixer and hydraulic press, with waste rubber content varying from 0 to 20 wt%. Mechanical properties were evaluated through tensile testing, thermal behavior was analyzed using TGA, DTG, and DSC, and long-term water absorption was measured. Results show that increasing waste rubber content from 0 to 20% led to a decrease in tensile strength (11.3 to 8.9 MPa) and tensile modulus (1760 to 790 MPa), while relative extension increased (2.4–5.9%). Thermal analysis revealed a slight reduction in onset degradation temperature (270 °C to 240 °C) and increased char residue (8–18%) with higher rubber content. Water absorption decreased significantly, from 12 to 13% to 6–7% after 600 h of immersion, as waste rubber content increased. These findings demonstrate that incorporating waste rubber into HDPE/barley straw composites results in materials with enhanced flexibility and water resistance at the cost of some strength and stiffness. In conclusion, the results of this study offer a clear pathway for the development of sustainable polymer composites that have broad potential applications across industries like construction, marine infrastructure, automotive, and packaging. By replacing traditional, resource-intensive materials with eco-friendly alternatives, these composites not only provide functional benefits but also support global efforts toward sustainable development and environmental conservation.