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Urban green space equity relates to the efficient allocation of natural resources and the equalization of public service facilities. Street (road) greenery provides substantial ecological, social and cultural benefits. Thus, in this study, a subdistrict-level evaluation framework for the fairness of the spatial distribution of street greenery was proposed, taking a case study within the Third Ring Road of Fuzhou City in Fujian, China. Street view images may capture the green information in a vertical dimension for the indirect representation of people's perspective on the ground. The green view index, which was estimated based on Baidu Street View images, was employed to represent the urban street greenery, and the results were combined using deep learning technology. The Gini coefficient, share index and location entropy were used as evaluation indicators for the fairness of the spatial distribution of the street green view index. Furthermore, this framework combined socioeconomic data and population census data to explore the correlation among socioeconomic status, age, and evaluation index at the subdistrict level. In addition, we analyzed street greenery distribution inequalities from the perspective of socioecological justice. The results showed that in Fuzhou, there is a significant correlation among the Gini coefficient, green view index and socioeconomic status. In addition, subdistricts with a lower green view index have a less equitable street greenery distribution, people with low socioeconomic status may suffer from green injustice, and seniors have a lower accessibility to street green space than people with the average social status. Our analytical approach is applicable for other cities, and the findings are useful for greenery spatial planning processes and evaluating construction effects. • Visible street greenery was evaluated using the green view index. • A framework for assessing the fairness of street greenery distribution was proposed. • Subdistricts in Fuzhou with a lower GVI value have more inequitable street greenery distributions. • Equitable access to green space is related to socioeconomic status and age. [ABSTRACT FROM AUTHOR]

[Display omitted] • The encoder-decoder-based network with multi-task learning is proposed. • Three self-supervised reconstruction tasks are established. • A low-quality fundus image is decomposed into three feature layers in the enhancement process. • An effective fusion strategy is designed based on the features of different layers. • Experiments prove that our method is superior in visual comparison and objective evaluation. Fundus images are used to assist the diagnoses of ocular diseases, and a high-quality fundus image with more details makes clinical diagnostic results more reliable. However, the quality of fundus images is often unsatisfactory due to the turbidity of refractive medium and the doctor-patient cooperation. To enhance the low-quality fundus images, a transformer-based self-supervised network is proposed. During the training phase, an encoder-decoder-based network is introduced. To counteract the drawbacks of establishing long-term dependencies in the convolutional neural network (CNN), the encoder composed of vision transformer and CNN is proposed so that the global and local information of fundus images is fully extracted. On this basis, three reconstruction tasks with self-supervised constraints are designed to enable the network to extract features from different degenerated images. During the testing phase, a low-quality fundus image is decomposed into three feature layers of reverse, illumination, and detail, and then the multi-layer features are fused via the network. To demonstrate the effectiveness of the proposed method, the non-uniform illumination and blurry fundus images are tested. The average scores of NIQE on underexposed, blurred, and overexposed fundus images are 3.03, 2.98, and 2.80, respectively. The average scores of BRISQUE on underexposed, blurred, and overexposed fundus images are 40.32, 40.55, and 39.76, respectively. The average score of subjective evaluation by three ophthalmologists is 61.17%. Compared with the existing methods, the proposed method achieves the superior performance in both subjective and objective evaluations. [ABSTRACT FROM AUTHOR]

• The increase of FA content improved SAAM's capacity to bind chloride. • CaAl-LDH was the most effective in reducing the content of free Cl-. • Chloride binding capacity of MgAl-LDH was compromised by less strength loss. The chloride binding mechanism of alkali-activated materials (AAM) under various granulated blast furnace slag (GBFS)/fly ash (FA) ratios is investigated in this work. Two types of layered double hydroxides (LDH), i.e., MgAl-LDH and CaAl-LDH, and active magnesium oxide (MgO) were added to reduce the concentration of free chloride in AAM. The results demonstrate that the ratio of GBFS to FA has non-negligible influence on the AAM's ability to bind chloride. The content of bound chloride increased by 3.78%-17.42% as the FA content in seawater-based alkali-activated materials (SAAM) raised. The chloride binding forms of SAAM were mainly chemical binding by the hydrated calcium aluminate (AFm) phase and physical adsorption by calcium (alumino) silicate hydration (C-(A)-S-H) gels when the FA dosage is less than 20% in SAAM. When the FA mass ratio in SAAM was larger than 20%, the chloride binding form of SAAM was mainly the physical adsorption by calcium (sodium) alumino-silicate hydrate ((C, N)-A-S-H) gels. Among the three additive materials, CaAl-LDH was the most effective in reducing the free chlorine content by 11.34%. While for MgAl-LDH, the chloride binding capacity was compromised by the less strength loss. In this work, seawater was used as the mixing water to introduce chloride ions, the results of which could provide a reference for the application of seawater in future projects. [ABSTRACT FROM AUTHOR]

• Protein stabilized PSNPs (BSA, CS > HSA > Col I) in NaCl solution except for BHb. • Protein destabilized PSNPs (HSA > BHb > Col I > BSA) in CaCl 2 solution except for CS. • Major factors were protein structure and concentration, electrolyte, and solution pH. • Protein showed strong adsorption affinity onto PSNPs and formed protein corona. • Main mechanisms were electrostatic interaction, steric hindrance and cation bridging. Aggregation kinetics of nanoplastics in aquatic environment are influenced by their interactions with proteins having different structures and properties. This study employed time-resolved dynamic light scattering (TR-DLS) to investigate the effects of 5 proteins (bovine hemoglobin (BHb), bovine (BSA) and human serum albumin (HSA), collagen type I (Col I), and bovine casein (CS)) on aggregation kinetics of polystyrene nanoplastics (PSNPs) under natural water conditions, which were simulated using various ionic strength (1-1000 mM NaCl and 0.01-100 mM CaCl 2), pH (3-9), and protein concentration (1-5 mg/L of total organic carbon). The results indicated that the interactions between proteins and PSNPs strongly depended on electrostatic properties, protein structures, and solution chemistries, which induced distinct aggregation behaviors in NaCl and CaCl 2 solutions. Electrostatic repulsion and steric hindrance dominated their interactions in NaCl solution by stabilizing PSNPs with the order of spherical BSA and disordered CS > heart-shaped HSA > fibrillar Col I; whereas positively charged BHb destabilized PSNPs with aggregation rate of 1.71 nm/s at 300 mM NaCl. In contrast, at CaCl 2 concentration below 20 mM, proteins destabilized PSNPs following the sequence of HSA > BHb > Col I > BSA depending on counterbalance among double layer compression, cation bridging, and steric hindrance; whereas CS stabilized PSNPs by precipitating Ca2+ that inhibited charge screening effect. Both protein concentration and solution pH affected protein corona formation, surface charge, and protein structure that altered stability of PSNPs. Characterizations using fluorescence spectroscopy, circular dichroism, and two-dimensional correlation analysis spectroscopy showed fluorescence quenching and ellipticity reduction of proteins, indicating strong adsorption affinity between PSNPs and proteins. The study provides insight to how protein configuration and water chemistry affect fate and transport of nanoplastics in aquatic environment. Graphical Abstract [Display omitted] [ABSTRACT FROM AUTHOR]

• Macromolecules stabilized PSNPs in NaCl but destabilized PSNPs in CaCl 2 solution. • Stabilization of PSNPs in NaCl solution followed the order of BSA > HA > EPS > SA. • Adsorption layer thickness and structure of macromolecules affected PSNP stability. • Higher SA and CaCl 2 concentrations enhanced PSNP destabilization by SA-Ca2+ bridging. • BSA, HA and EPS destabilized PSNPs in Ca2+ by molecular bridging and EDL compression. Nanoplastics derived from degradation of micro- or macroplastics are emerging contaminants in aquatic environments, where their fate and transport as well as toxicity are affected by aggregation. This study employed time-resolved dynamic light scattering to investigate the aggregation kinetics of polystyrene nanoplastics (PSNPs) in the presence of four macromolecules (sodium alginate (SA), bovine serum albumin (BSA), extracellular polymeric substance (EPS), and Suwannee River humic acid (HA)) in solutions containing monovalent (NaCl) and divalent (CaCl 2) salts at different pH. Our results showed that the macromolecules enhanced PSNP stability in NaCl solutions but destabilized PSNPs in CaCl 2 solutions at pH 6. In NaCl solutions, macromolecules inhibited PSNP aggregation due to steric hindrance originated from macromolecular layer adsorbed on PSNPs. The strongest stabilization effect was observed for BSA having the greatest hydrodynamic adsorption layer thickness of 21.9 nm, followed by HA, EPS, and SA. In CaCl 2 solutions, SA significantly destabilized PSNPs via alginate bridging with Ca2+, which enhanced with concentrations of SA and CaCl 2. The destabilization effects of other three macromolecules in CaCl 2 solutions were governed by the interplay among molecular bridging, charge screening, and steric hindrance. An increased pH in NaCl or CaCl 2 solutions containing macromolecules all stabilized PSNPs due to elevated electrostatic repulsion, except that SA destabilized PSNPs in CaCl 2 solutions via enhanced molecular bridging. The stabilization effect of macromolecules may also compete with the destabilization effect under seawater condition. This study suggested that PSNP aggregation in aquatic environments could be strongly affected by macromolecules and solution chemistry. Image, graphical abstract [ABSTRACT FROM AUTHOR]

• The interaction between TC and Cd could alleviate the toxic effects of TC/Cd on aerial rice structures. • The single/combined exposure of TC and Cd at low doses promoted rice root elongation but had the opposite effect at high doses. • The combined pollutions allowed an increase in Cd transport and a decrease in TC transport. • LA-ICP MS observed that Cd mainly accumulated in the epidermis and stele of the root, while Fe mainly accumulated in the epidermal area. Co-exposure to heavy metal and antibiotic pollution might result in complexation and synergistic interactions, affecting rice growth and further exacerbating pollutant enrichment. Therefore, our study sought to clarify the influence of different Tetracycline (TC) and Cadmium(Cd) concentration ratios (both alone and combined) on rice growth, pollutant accumulation, and transportation during the tillering stage in hydroponic system. Surprisingly, our findings indicated that the interaction between TC and Cd could alleviate the toxic effects of TC/Cd on aerial rice structures and decrease pollutant burdens during root elongation. In contrast, TC and Cd synergistically promoted the accumulation of TC/Cd in rice roots. However, their interaction increased the accumulation of TC in roots while decreasing the accumulation of Cd when the toxicant doses increased. The strong affinity of rice to Cd promoted its upward transport from the roots, whereas the toxic effects of TC reduced TC transport. Therefore, the combined toxicity of the two pollutants inhibited their upward transport. Additionally, a low concentration of TC promoted the accumulation of Cd in rice mainly in the root tip. Furthermore, a certain dose of TC promoted the upward migration of Cd from the root tip. Laser ablation-inductively coupled plasma mass spectrometry demonstrated that Cd mainly accumulated in the epidermis and stele of the root, whereas Fe mainly accumulated in the epidermis, which inhibited the absorption and accumulation of Cd by the rice roots through the generation of a Fe plaque. Our findings thus provide insights into the effects of TC and Cd co-exposure on rice growth. [ABSTRACT FROM AUTHOR]

Compressed sensing (CS) has been applied for image compression and encryption, for it may compress and encrypt images simultaneously. However, some CS-based image encryption algorithms still suffer from low security and compression performance. To solve these problems, a content-adaptive compression-encryption based on CS and RiboNucleic Acid (RNA) is proposed in this paper. Firstly, the 4D laser chaos system was used to construct a measurement matrix for image compression. Secondly, an Improved Fractal Sorting Matrix (IFSM) and its iterative approach are introduced based on the Fractal Sorting Matrix (FSM) for permutation. It has the same characteristics as FSM, but with a greater permutation effect and a broader range of applications. Finally, an adaptive RNA diffusion is designed based on the unique codon of RNA, which includes codon substitution and calculation operations. This adaptive operations make the algorithm more difficult to crack. Additionally, chaotic sequences driven by the hash value of plain image are utilized in the whole encryption, which enhances the correlation between the algorithm and plain image and improves the ability to resist known-plaintext and chosen-plaintext attacks. Experimental results and performance analyses demonstrate that the proposed scheme has excellent security and compression property. [ABSTRACT FROM AUTHOR]

High-quality fundus images are essential for ophthalmologists in clinical diagnosis of eye diseases. For reasons such as the acquisition process and the retinal disease, most fundus images may suffer poor illumination, blur, and low contrast. In order to obtain high-quality fundus images, a novel network model for fundus image enhancement is constructed in this paper. The model introduces a generated adversarial network (GAN) with illumination-guided attention and optic disc perception. A U-Net with illumination-guided attention is used as the generator, and a global discriminator and a local discriminator with optic disc segmentation are used in the learning process. The model can improve the exposure level of overexposed and underexposed fundus images and also stretch the contrast. Experiments are performed on multiple fundus image datasets taken by the handheld device and high-end device to verify the robustness of the proposed illumination-guided attention and optic disc perception GAN (IGAODPGAN). The retinal structure and pathological characteristics are highlighted significantly after enhancement. Our method is superior to other state-of-the-art algorithms in terms of both subjective and objective assessment, which can provide an efficient solution for fundus image enhancement, especially for the non-uniform illuminated fundus images. [ABSTRACT FROM AUTHOR]