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Electrospun nanofibrous membranes (eNFMs) have been extensively developed for bio-applications due to their structural and compositional similarity to the natural extracellular matrix. However, the emergence of antibiotic resistance in bacterial infections significantly impedes the further development and applications of eNFMs. The development of antibacterial nanomaterials substantially nourishes the engineering design of antibacterial eNFMs for combating bacterial infections without relying on antibiotics. Herein, a comprehensive review of diverse fabrication techniques for incorporating antibacterial nanomaterials into eNFMs is presented, encompassing an exhaustive introduction to various nanomaterials and their bactericidal mechanisms. Furthermore, the latest achievements and breakthroughs in the application of these antibacterial eNFMs in tissue regenerative therapy, mainly focusing on skin, bone, periodontal and tendon tissues regeneration and repair, are systematically summarized and discussed. In particular, for the treatment of skin infection wounds, we highlight the antibiotic-free antibacterial therapy strategies of antibacterial eNFMs, including (i) single model therapies such as metal ion therapy, chemodynamic therapy, photothermal therapy, and photodynamic therapy; and (ii) multi-model therapies involving arbitrary combinations of these single models. Additionally, the limitations, challenges and future opportunities of antibacterial eNFMs in biomedical applications are also discussed. We anticipate that this comprehensive review will provide novel insights for the design and utilization of antibacterial eNFMs in future research.

Background and purposeRadiotherapy is a primary therapeutic approach for breast cancer following breast-conserving surgery. The TaiChiB dual-modality radiotherapy system combining X-ray and focused γ-ray, offers a new approach to reduce the radiation dose of organs at risk (OARs) and has the potential to mitigate the adverse effects of radiotherapy. Currently, there are few studies on the dosimetric characteristics of the TaiChiB dual-modality system for actual treatment plans for specific diseases. The purpose of this work is to study the dosimetric advantages of dual-modal systems for right breast patients after breast-conserving surgery.Material and methodsTreatment plans for 20 patients with right breast cancer were generated for a linear accelerator (LINAC) based system and the TaiChiB dual-modality system, respectively. Volumetric modulated arc therapy plans with simultaneous integrated boost (VMAT-SIB) were made for the LINAC. Focused γ-ray was used to deliver the boost dose with the dual-modality system. The dosimetric parameters of the target and OARs were evaluated and compared between the treatment plans generated for the two systems.ResultsThe TaiChiB dual-modality plans exhibit a higher conformal index (CI) and lower gradient index (GI) for the PGTV and PTV compared with the LINAC-based VMAT-SIB plans. Compared to VMAT-SIB plans, the PTV Dmax, PTV Dmean, PTV V110, PGTV Dmax, and PGTV Dmean of the TaiChiB dual-modality plans are significantly lower. Meanwhile, the dose to OARs, such as the Dmean of the heart, the V5 of liver, the Dmean of ipsilateral lung, the V30 of ipsilateral lung, the V20 of ipsilateral lung, the V5 of ipsilateral lung, the Dmean of contralateral lung, Dmax of contralateral breast and the Dmean of contralateral breast are significantly reduced.ConclusionsOur study demonstrates the dosimetric advantages of the novel TaiChiB dual-modality radiotherapy system for the treatment of right-sided breast cancer. Overall, for the TaiChiB dual-modality radiotherapy system, the radiation dose outside the target region decreases rapidly, thereby minimizing radiation exposure to neighboring organs and ensuring the conformity of the target area. Our research confirms the potential of the TaiChiB dual-modality system for future radiotherapy.

When subjected to a vessel collision in the presence of scour induced by wave-current or flood, a bridge can sustain more severe damage compared to the pristine bridge undergoing the same impact. Scouring diminishes the ultimate capacity of pile foundations and can result in local damage to piers and pile foundations post-collision. This study aimed to mitigate impact damage on a scoured steel reinforced concrete (RC) bridge by employing a concrete-filled steel tubular pier and increasing the pile foundation section area. Pendulum impact tests were conducted on four concrete-filled steel-tubular pier-pile foundation systems to study their impact behaviors with scour depth effects. Experimental results show that while the displacement at the top of the pier increases with scour depth, there is no observed local damage to the impacted pier, even at deep scour depths. Subsequently, an FE model of the steel RC bridge was developed to assess the local dynamic behavior and damage based on the validated model. The impact performance of the scoured bridge, reinforced with a concrete-filled steel tubular pier and an increased pile section area, was then evaluated. Compared to the pristine bridge, the pile foundation with scour is prone to yield under the same impact condition, especially at deep scour depths. The increased section area method significantly enhances impact performance and reduces potential local damage to pile foundations, even under deep scour conditions. Additionally, a concrete-filled steel tubular pier markedly improves impact behavior compared to a conventional RC bridge pier. These findings underscore the efficacy of structural enhancements in bolstering the resilience of bridges against vessel collisions in scour-prone environments.

Abstract In the field of world heritage conservation, there has been broad consensus on carrying out heritage conservation research on the basis of spatial integration and interregional and international cooperation. However, there are still many deficiencies in the integration of culture with the environment, regional economic and social development, and the regional, holistic and multimodal conservation and utilization of cultural heritage sites. In China, the Dongjiang-Hanjiang River Basin is a representative area of substantial cultural and ecological value for both Guangdong Province and the whole country. This paper uses the morphological spatial pattern analysis and the minimum cumulative resistance model to integrate cultural ecology sources and establish a cross-regional and large-scale cultural ecology network system that includes 1 main corridor, 22 important corridors and 17 secondary corridors. In addition, based on identified cultural landscape nodes and cultural ecology services, the economy of the cultural ecology corridor could be developed with large-scale co-construction, co-governance and shared working mechanisms to overcome administrative limits and realize the conservation and utilization of multimodal and large-scale heritage sites. This approach has strong theoretical and practical significance for innovative methods in cultural ecology research, as well as for new content in the research of Lingnan culture, ecosystem restoration, and the economic and social development of towns and villages. This article supplements unilateral studies of regional culture and ecology and demonstrates an in-depth application of cultural ecology theory.

This paper established a mathematical model with nonconvex bilinear terms. It formulated the complex material flow in the petroleum refinery scenario based on the concept of the "P model". The mathematical model described the nonlinear constraints such as linear and nonlinear mass and volume intersection flow blending of crude and middle material physical properties. Additionally, it described the complex inflow and outflow in secondary devices as nonlinear constraints such as delta-base structure and physical property transfer. It is highly difficult to determine the direction and quantity of each material in the network of refineries. An improved interior point algorithm with an initial point strategy was proposed to find a high-quality feasible solution in a short time. The real instances from the petroleum refinery were employed to compare and analyze the solutions from the improved algorithm and commercial solver. The experimental results show that the proposed algorithm framework can balance the solution quality and computational efficiency and perform well in different scenarios of refinery material flow networks.

Building pattern recognition is important for understanding urban forms, automating map generalization, and visualizing 3D city models. However, current approaches based on object-independent methods have limitations in capturing all visually aware patterns due to the part-based nature of human vision. Moreover, these approaches also suffer from inefficiencies when applying proximity graph models. To address these limitations, we propose a framework that leverages multi-scale data and a knowledge graph, focusing on recognizing C-shaped building patterns. We first employ a specialized knowledge graph to represent the relationships between buildings within and across various scales. Subsequently, we convert the rules for C-shaped pattern recognition and enhancement into query conditions, where the enhancement refers to using patterns recognized at one scale to enhance pattern recognition at other scales. Finally, rule-based reasoning is applied within the constructed knowledge graph to recognize and enrich C-shaped building patterns. We verify the effectiveness of our method using multi-scale data with three levels of detail (LODs) collected from AMap, and our method achieves a higher recall rate of 26.4% for LOD1, 20.0% for LOD2, and 9.1% for LOD3 compared to existing methods with similar precision rates. We also achieve recognition efficiency improvements of 0.91, 1.37, and 9.35 times, respectively.

Satellite multi-view stereo (MVS) is a fundamental task in large-scale Earth surface reconstruction. Recently, learning-based multi-view stereo methods have shown promising results in this field. However, these methods are mainly developed by transferring the general learning-based MVS framework to satellite imagery, which lacks consideration of the specific terrain features of the Earth’s surface and results in inadequate accuracy. In addition, mainstream learning-based methods mainly use equal height interval partition, which insufficiently utilizes the height hypothesis surface, resulting in inaccurate height estimation. To address these challenges, we propose an end-to-end terrain feature-aware height estimation network named SA-SatMVS for large-scale Earth surface multi-view stereo, which integrates information across different scales. Firstly, we transform the Sobel operator into slope feature-aware kernels to extract terrain features, and a dual encoder–decoder architecture with residual blocks is applied to incorporate slope information and geometric structural characteristics to guide the reconstruction process. Secondly, we introduce a pixel-wise unequal interval partition method using a Laplacian distribution based on the probability volume obtained from other scales, resulting in more accurate height hypotheses for height estimation. Thirdly, we apply an adaptive spatial feature extraction network to search for the optimal fusion method for feature maps at different scales. Extensive experiments on the WHU-TLC dataset also demonstrate that our proposed model achieves the best MAE metric of 1.875 and an RMSE metric of 3.785, which constitutes a state-of-the-art performance.

Abstract Deep learning has recently been proven to deliver excellent performance in multi-view stereo (MVS). However, it is difficult for deep learning-based MVS approaches to balance their efficiency and effectiveness. Towards this end, we propose the DSC-MVSNet, a novel coarse-to-fine and end-to-end framework for more efficient and more accurate depth estimation in MVS. In particular, we propose an attention aware 3D UNet-shape network, which first uses the depthwise separable convolutions for cost volume regularization. This mechanism enables effective aggregation of information and significantly reduces the model parameters and computation by transforming the ordinary convolution on cost volume as depthwise convolution and pointwise convolution. Besides, a 3D-Attention module is proposed to alleviate the feature mismatching problem in cost volume regularization and aggregate the important information of cost volume in three dimensions (i.e. channel, space, and depth). Moreover, we propose an efficient Feature Transfer Module to upsample the low-resolution (LR) depth map to a high-resolution (HR) depth map to achieve higher accuracy. With extensive experiments on two benchmark datasets, i.e. DTU and Tanks & Temples, we demonstrate that the parameters of our model are significantly reduced to $$25\%$$ 25 % of the state-of-the-art model MVSNet. Besides, our method outperforms or maintains on par accuracy with the state-of-the-art models. Our source code is available at https://github.com/zs670980918/DSC-MVSNet .

New materials for combating bacteria-caused infection and promoting the formation of microvascular networks during wound healing are of vital importance. Although antibiotics can be used to prevent infection, treatments that can disinfect and accelerate wound healing are scarce. Herein, we engineer a coating that is both highly compatible with current wound dressing substrates and capable of simultaneously disinfecting and revascularizing wounds using a metal-phenolic nanoplatform containing an alloyed nanostructured architecture (Ag@Cu-MPNNC). The alloyed nanostructure is formed by the spontaneous co-reduction and catalytic disproportionation reaction of multiple metal ions on a foundation metal-phenolic supramolecular layer. This synergistic presence of metals greatly improves the antibacterial activity against both Gram-negative and Gram-positive pathogenic bacteria, while demonstrating negligible cytotoxicity to normal tissue. In infected rat models, the Ag@Cu-MPNNC could kill bacteria efficiently, promoting revascularization and accelerate wound closure with no adverse side effects in infected in vivo models. In other words, this material acts as a combination therapy by inhibiting bacterial invasion and modulating bio-nano interactions in the wound.

In the integrated generalization of contours and rivers, it is more important to consider the generalization of their geographical characteristics in addition to focusing on the graph generalization. Therefore, we elaborated on the geographical characteristics on which the contours and rivers depend in the integrated generalization, qualitatively describe and quantitatively characterize the geographical characteristics (spatial characteristics and geographical elements information content characteristics), and put forward the integrated generalization method of contours and rivers considering geographical characteristics. Based on the geographical characteristics, this article first identifies the relief and river network morphology, then as an essential terrain constraint, the spatial analysis and selection of topographic feature lines were carried out. Second, according to the integrated generalization method, the contours and rivers were discretized into 3D points along with describing semantic information and giving weights. Finally, the integrated generalization considering geographical characteristics experiment was implemented and well generalization results were obtained.

Silicon photonics has been studied in various areas by providing small-footprint, high-performance, and mass-producible optoelectronic components integrated on a chip. For the photonic packaging, ultraviolet (UV) curing techniques have been widely utilized. Meanwhile, silica cladding absorption to UV light could alter its refractive index (RI), affecting the optical testing of silicon devices during or after the device packaging. Therefore, it is significant to characterize the dynamics of RI changes induced by UV-light irradiation. However, the in-situ characterization of such devices is seldom explored. Here, we studied the influence of UV-light irradiation on silicon photonic devices by probing resonant wavelength shifts of a racetrack microring resonator. Specifically, we studied the temporary variation of the resonant wavelength and its recovery time under different UV-light exposure durations. Experimental results show that with a UV energy of 21 J/cm2, the resonator had a maximum resonant wavelength shift of 0.31 nm, corresponding to an effective RI change of 0.0009 and recovering time of 95 minutes. Based on the experimental results, we compressively analyzed and compared RI changes induced by plasmon dispersion effect, thermal optical effect and photon-induced silica densification effect. Our study is expected to provide useful guidelines for in-situ silicon photonic testing and packaging.

Patients with chronic kidney disease are at high risk of hyperkalemia that is associated with various life-threatening complications. Treatments primarily rely on orally administered potassium binding agents, along with low curative effects and various side effects. Herein, direct serum potassium uptake was realized via zeolite–heparin-mimicking-polymer hybrid microbeads. The preparation process involved the synthesis of the heparin-mimicking polymer via the in situ cross-linking polymerization of acrylic acid and N-vinylpyrrolidone in polyethersulfone solution, the fabrication of microbeads via zeolite-mixing, electro-spraying and phase-inversion, and the subsequent aqueous-phase modifications based on ion-exchange and metal-leaching. An ultra-high (about 88%) amount of zeolite could be incorporated and well locked inside the polymer matrix. Potassium uptake capability was verified in water, normal saline and human serum, showing high selectivity and fast adsorption. The microbeads exhibited satisfying blood compatibility, negligible hemolysis ratio, prolonged clotting time, inhibited contact activation, and enhanced antifouling property toward serum proteins and cells. The proposed approach toward zeolite–heparin-mimicking-polymer hybrid microbeads provided a cheap, efficient and safe treatment protocol of hyperkalemia for the high-risk patients.

Melatonin is involved in plant responses to various environmental stresses. Although many studies have demonstrated that the tolerance of plants to stress is improved by exogenous melatonin, the role of endogenous melatonin metabolism in the response of apples to UV-B stress remains unclear. Here, the human melatonin biosynthesis-related enzyme genes AANAT or HIOMT were transformed into 'GL-3' apple, and the transgenic lines were treated with UV-B stress. The ectopic expression of AANAT or HIOMT significantly increased the melatonin content in apples. After UV-B stress, the tolerance of apple lines with ectopic expression of AANAT or HIOMT was markedly improved. The decrease in chlorophyll fluorescence, the generation of reactive oxygen species and the shrinkage of stomata caused by UV-B stress were alleviated by AANAT or HIOMT ectopic expression. In addition, the total phenolic content was markedly increased in the transgenic lines compared with the WT (wild type). The increase in phenolic compounds was related to the increase in benzoic acid, hydroxycinnamic acid, dihydrochalcones and flavanols, among which increases in chlorogenic acid, phloridzin and procyanidin B1 content were most prominent. Furthermore, the transgenic lines did not only promote the expression of genes related to phenolic synthesis under UV-B stress, but they also increased the accumulation of phenolic compounds by inhibiting the expression of MdPPO and MdPOD related to phenolic degradation. In summary, our results demonstrate that AANAT- or HIOMT-mediated melatonin synthesis improved the tolerance of apples to UV-B stress, mainly by scavenging reactive oxygen species, increasing photosynthetic capacity and increasing total phenolic content.

On-chip optical gas sensors, which use resonant shifts of cavities to detect molecular concentrations, have the advantages of high sensitivity, real-time detection, and compact footprint. However, such sensors are usually limited by a serious cross-sensitivity issue induced by environmental temperature variations. To overcome this limitation, we study a dual-mode graphene-on-microring resonator to accurately measure gas concentrations without suffering from temperature variations. To be specific, the influences of gas-induced graphene’s optical conductivity changes and environmental temperature variations on effective refractive indices of TE0 and TE1 modes in the resonator can be decoupled based on the modal linear independent responses. With this method, we designed a nitrogen dioxide sensor with a sensitivity of 0.02 nm/ppm and a limit of detection of 0.5 ppm. Our study paves the way for developing on-chip optical gas sensors with excellent sensitivity and temperature stability.

The on-chip mode-division multiplexing (MDM) is an attractive technique to achieve high-capacity optical transmissions by using a single-wavelength carrier. In traditional schemes, multiple channels with a fundamental mode are modulated by parallel arranged electro-optic modulators and then converted to high-order modes. However, the method is usually limited by large device footprints and high energy consumption. In this work, we study a graphene-based waveguide-integrated multimode phase modulator to individually modulate TE0 and TE1 modes in a multimode waveguide device. To be specific, we designed a single layer of graphene narrow strips (GNSs) integrated on the surface of the multimode waveguide device to selectively introduce contrasting phase shifts to different modes. Based on the optimized waveguide structures, a Mach-Zehnder interferometer modulator with different GNS patterns on each arm is designed. Our study is promising to be used in the future high-density on-chip MDM systems for optical interconnects and optical networks.

The classification of motor imagery Electroencephalogram (EEG) of the same limb is important for natural control of neuroprosthesis. Due to the close spatial representations on the motor cortex area of the brain, the discrimination of the different motor imagery tasks is challenging. In this paper, phase synchronization information was proposed to classify motor imagery EEG within the same limb. In addition, non-portable was compared with portable EEG acquisition equipment for the purpose of making the brain computer interface (BCI) system more practical. In the non-portable case, the average accuracy of the binary classification and 3-class classification was 60.6% and 42.7%. In the portable case, the average EEG decoding accuracy of 58.5% and 39.9% was achieved for the two and three tasks. Furthermore, in both two cases, different sets of electrode pairs got the similar results. Moreover, we found that the proposed phase information based method was less sensitive to the number of EEG channels and had less performance degradation in portable EEG equipment. These results show it is possible to use phase synchronization information to discriminate different motor imagery tasks within the same limb. Eventually, this will potentially make the control of neuroprosthesis or other rehabilitation device more natural and intuitive.

A large amount of light crude oils have been found within 4000 to 7000 m deep strata of Cambrian, Ordovician, and Silurian reservoirs in the Tarim Basin, NW China. To enhance the understanding of parental materials of deep oils, a set of high-quality source rocks from the Yuertusi Formation in well Luntan 1 (maximum drilling depth of 8882 m) was studied in terms of their sedimentary condition and mechanism of organic matter enrichment. Total organic carbon (TOC) content, carbon isotope of kerogen (δ13Cker), and major and trace elements of the rocks from the Sinian Qigebulake, Cambrian Yuertusi, and Xiaoerbulake Formations in well Luntan 1 were analysed. The results showed that the δ13Cker value of the Yuertusi Formation barely changed with an average of -31.19‰. High TOC contents accompanied by enrichments of the bioessential trace elements, such as cadmium, chromium, copper, nickel, and zinc, occurred in the lower part of the Yuertusi Formation. Excess barium (Baxs) and phosphorus concentrations revealed high primary productivity during the deposition of the Yuertusi Formation. Moreover, variations in the enrichment factors of molybdenum, uranium, and vanadium and molybdenum-uranium covariation pattern indicated suboxic-anoxic conditions in the Qigebulake Formation, anoxic-euxinic conditions in the Yuertusi Formation, and suboxic-oxic conditions in the Xiaoerbulake Formation. The TOC contents were significantly correlated with the paleoproductivity and paleoredox parameters, indicating that high productivity and reducing conditions jointly controlled the organic matter accumulation and preservation in well Luntan 1.

Abstract Background Improvement of water-use efficiency (WUE) can effectively reduce production losses caused by drought stress. A better understanding of the genetic determination of WUE in crops under drought stress has great potential value for developing cultivars adapted to arid regions. To identify the genetic loci associated with WUE and reveal genes responsible for the trait in apple, we aim to map the quantitative trait loci (QTLs) for carbon isotope composition, the proxy for WUE, applying two contrasting irrigating regimes over the two-year experiment and search for the candidate genes encompassed in the mapped QTLs. Results We constructed a high-density genetic linkage map with 10,172 markers of apple, using single nucleotide polymorphism (SNP) markers obtained through restriction site-associated DNA sequencing (RADseq) and a final segregating population of 350 seedlings from the cross of Honeycrisp and Qinguan. In total, 33 QTLs were identified for carbon isotope composition in apple under both well-watered and drought-stressed conditions. Three QTLs were stable over 2 years under drought stress on linkage groups LG8, LG15 and LG16, as validated by Kompetitive Allele-Specific PCR (KASP) assays. In those validated QTLs, 258 genes were screened according to their Gene Ontology functional annotations. Among them, 28 genes were identified, which exhibited significant responses to drought stress in ‘Honeycrisp’ and/or ‘Qinguan’. These genes are involved in signaling, photosynthesis, response to stresses, carbohydrate metabolism, protein metabolism and modification, hormone metabolism and transport, transport, respiration, transcriptional regulation, and development regulation. They, especially those for photoprotection and relevant signal transduction, are potential candidate genes connected with WUE regulation in drought-stressed apple. Conclusions We detected three stable QTLs for carbon isotope composition in apple under drought stress over 2 years, and validated them by KASP assay. Twenty-eight candidate genes encompassed in these QTLs were identified. These stable genetic loci and series of genes provided here serve as a foundation for further studies on marker-assisted selection of high WUE and regulatory mechanism of WUE in apple exposed to drought conditions, respectively.

Spatial conflicts can remain unresolved during map generalization if only displacement is used, especially for urban building maps. To solve all possible spatial conflicts during urban building map generalization, we propose a collaborative displacement method, combining aggregation, elimination, and constrained reshape. After applying an improved vector field-based displacement for solution of initial conflicts, two types of sequential conflicts are detected and evaluated to identify additional displacement solutions based on a trial and error strategy. If no displacement solution is available, aggregation, elimination, or constrained reshape are selected and applied for the unsolved sequential conflicts based on cartographic rules. For a more reasonable generalization result, an improved constrained reshape approach is also introduced for buildings in conflicts along roads. Two data sets with scales of 1:5000 and 1:25000 for urban building map were selected to validate this approach. The results indicate that it is reasonable and feasible to solve all defined spatial conflicts in urban building map generalization using our proposed method.

In automatic map compilation, both the scale reduction and the geometric transformation of map features may give rise to spatial conflicts. Several generalization approaches have been established to resolve this problem, mainly for the displacement operator. This paper proposes one such approach that is based on the snake model and multiple agents. It focuses on the resolution of various spatial conflicts that emerge when generalizing the rural areas of medium density. In this approach, the map features are converted into map agent, object agent, group agent, and conflicting agent, and the spatial relationships between these features are managed by an auxiliary relationship agent. Each agent is assigned with tasks accordingly, and all agents collaborate with each other to complete the generalization. The snake-based algorithm is applied in the conflicting agent when it identifies a certain configuration. The experimental results indicate that the approach proposed in this paper can obtain good results.

Several algorithms have been developed to simplify buildings based on their local structure in past decades. However, different local structures are defined for certain purposes, and no algorithm can appropriately simplify all buildings. We propose a combined building simplification approach based on local structure classification and backtracking strategy. In this approach, local structures are classified and their based operations are defined by considering the buildings’ orthogonal and non-orthogonal features. Each building is simplified to target scale with a selected local-structure-based operation progressively scale-by-scale. Rules are built to support the selection of local-structure-based operations with a binary decision tree, and a backtracking strategy is used when an invalid operation is applied. When the building is too small or the evaluation shows that it cannot be simplified based on local structures, template matching or enlargement algorithms are applied to simplify the building. A dataset (1:10k) collected from the Ordnance Survey was used for the experiment and simplified scale of 1:25k. Results satisfied legibility constraints and the change in area, orientation and position of simplified buildings are controlled within certain range by comparing with the results generated based on other four simplification algorithms. Possible use of our approach for continuous scale transformation of buildings is also discussed.

The frequency and intensity of water deficits is expected to increase because of global warming. Drought stress is often one of the most limiting factors for plant growth. We conducted greenhouse pot experiments to address how dopamine affects the drought-resistance traits of apple trees at the physiological and molecular levels. Our factorial design consisted of dopamine and no-dopamine applications combined with well-watered and moderate-drought conditions. Seedling biomass, photosynthesis rates, chlorophyll concentrations, and stomatal apertures were markedly reduced under stress but dopamine treatment mitigated the inhibiting effects of drought on plant growth and helped maintain strong photosynthesis, chlorophyll levels, and stomatal functioning. Concentrations of most macro-, micro-, and trace elements decreased in response to drought. This stress also diminished the uptake and transport of elements in the leaves and stems, but increased the partitioning of elements in the roots. Nutrient resorption proficiency decreased while nutrient resorption efficiency increased for most analyzed elements. Exogenous dopamine significantly increased the concentrations, uptake, and transport of nutrients under drought stress, and also altered their distribution within the whole plant. However, this molecule had a negative effect on nutrient resorption. Although transcript levels of a key chlorophyll degradation gene, pheide a oxygenase, and senescence-associate gene 12 were elevated upon drought treatment, dopamine significantly suppressed the upregulation of those genes under such stress conditions. These observations indicate that dopamine has an important anti-senescence effect that might be helpful for regulating nutrient uptake, transport, and resorption, and ultimately influencing overall plant growth. Thus, understanding the role of dopamine in drought tolerance introduces new possibilities to use this compound for agricultural purposes.

In map generalization, scale reduction and feature symbolization inevitably generate problems of overlapping objects or map congestion. To solve the legibility problem with respect to the generalization of dispersed rural buildings, selection of buildings is necessary and can be transformed into an optimization problem. In this paper, an improved genetic algorithm for building selection is designed to be able to incorporate cartographic constraints related to the building selection problem. Part of the local constraints for building selection is used to constrain the encoding and genetic operation. To satisfy other local constraints, a preparation phase is necessary before building selection, which includes building enlargement, local displacement, conflict detection, and attribute enrichment. The contextual constraints are used to ascertain a fitness function. The experimental results indicate that the algorithm proposed in this article can obtain good results for building selection whilst preserving the spatial distribution characteristics of buildings.