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Auxin Response Factors (ARFs) make up a plant-specific transcription factor family that mainly couples perception of the phytohormone, auxin, and gene expression programs and plays an important and multi-faceted role during plant growth and development. Lemongrass (Cymbopogon flexuosus) is a representative Cymbopogon species widely used in gardening, beverages, fragrances, traditional medicine, and heavy metal phytoremediation. Biomass yield is an important trait for several agro-economic purposes of lemongrass, such as landscaping, essential oil production, and phytoremediation. Therefore, we performed gene mining of CfARFs and identified 26 and 27 CfARF-encoding genes in each of the haplotype genomes of lemongrass, respectively. Phylogenetic and domain architecture analyses showed that CfARFs can be divided into four groups, among which groups 1, 2, and 3 correspond to activator, repressor, and ETTN-like ARFs, respectively. To identify the CfARFs that may play major roles during the growth of lemongrass plants, RNA-seq was performed on three tissues (leaf, stem, and root) and four developmental stages (3-leaf, 4-leaf, 5-leaf. and mature stages). The expression profiling of CfARFs identified several highly expressed activator and repressor CfARFs and three CfARFs (CfARF3, 18, and 35) with gradually increased levels during leaf growth. Haplotype-resolved transcriptome analysis revealed that biallelic expression dominance is frequent among CfARFs and contributes to their gene expression patterns. In addition, co-expression network analysis identified the modules enriched with CfARFs. By establishing orthologous relationships among CfARFs, sorghum ARFs, and maize ARFs, we showed that CfARFs were mainly expanded by whole-genome duplications, and that the duplicated CfARFs might have been divergent due to differential expression and variations in domains and motifs. Our work provides a detailed catalog of CfARFs in lemongrass, representing a first step toward characterizing CfARF functions, and may be useful in molecular breeding to enhance lemongrass plant growth. [ABSTRACT FROM AUTHOR]

This study was conducted in response to the Beijing–Tianjin–Hebei mega heavy rainfall event at the end of July 2023, and the severely affected and representative Jiangou village in Beijing was selected as the study area. A variety of methods were used to synthesize and analyze the situation and propose an adaptive response to heavy rainfall and flooding in the village. Based on multi-source remote sensing (RS) data, a comprehensive topographic and hydrological characterization was carried out, and the precipitation before and after the disaster was analyzed; the flood inundation area was extracted using the improved normalized water body index (MNDWI) and OTSU thresholding methods, and the changes of water bodies during the flooding period were quantitatively analyzed; and an improved convolutional-neural-network-based building identification and extraction model was constructed to extract the research distribution of buildings in the area. The sponge city construction (SPCC) method was improved to obtain a method that can mitigate flood risk and adapt to villages by constructing small artificial lakes and local topographic buffers to improve the water storage and drainage capacity of villages. The study shows that these methods are innovative in flood hazard analysis and mitigation but still need further improvement in data accuracy, simulation depth, and system evaluation. [ABSTRACT FROM AUTHOR]

Accurate digital mapping of farmland soil organic carbon (SOC) contributes to sustainable agricultural development and climate change mitigation. Farmland landscape pattern has changed greatly under anthropogenic influence, which should be considered an environmental variable to characterize the impact of human activities on SOC. In this study, we verified the feasibility of integrating landscape patterns in SOC prediction on Lower Liaohe Plain. Specifically, ten variables (climate, topographic, and landscape pattern variables) were selected for prediction with Random Forest (RF) and Support Vector Machines (SVMs). The effectiveness of landscape metrics was verified by establishing different variable combinations: (1) natural variables, and (2) natural and landscape pattern variables. The results confirmed that landscape variables improved mapping accuracy compared with natural variables. R2 of RF and SVM increased by 20.63% and 20.75%, respectively. RF performed better than SVM with smaller prediction error. Ranking of importance of variables showed that temperature and precipitation were the most important variables. The Aggregation Index (AI) contributed more than elevation, becoming the most important landscape variable. The Mean Contiguity Index (CONTIG-MN) and Landscape Contagion Index (CONTAG) also contributed more than other topographic variables. We conclude that landscape patterns can improve mapping accuracy and support SOC sequestration by optimizing farmland landscape management policies. [ABSTRACT FROM AUTHOR]

Among so many autonomous driving technologies, autonomous lane changing is an important application scenario, which has been gaining increasing amounts of attention from both industry and academic communities because it can effectively reduce traffic congestion and improve road safety. However, most of the existing researchers transform the multi-objective optimization problem of lane changing trajectory into a single objective problem, but how to determine the weight of the objective function is relatively fuzzy. Therefore, an optimization method based on the combination of the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), which provides a new idea for solving the multi-objective optimization problem of lane change trajectory algorithm, is proposed in this paper. Firstly, considering the constraints of lane changing and combining with the collision detection algorithm, the feasible lane changing trajectory cluster is obtained based on the quintic polynomial. In order to ensure the comfort, stability and high efficiency of the lane changing process, the NSGA-II Algorithm is used to optimize the longitudinal displacement and time of lane changing. The continuous ordered weighted averaging (COWA) operator is introduced to calculate the weights of three objective optimization functions. Finally, the TOPSIS Algorithm is applied to obtain the optimal lane change trajectory. The simulations are conducted, and the results demonstrate that the proposed method can generate a satisfactory trajectory for automatic lane changing actions. [ABSTRACT FROM AUTHOR]

Converting floodwater into power without increasing flood risk is critical for energy-stressed regions. Over the past decades, numerous methods have been proposed to solve this problem. However, few studies have investigated the theoretical explanation of the trade-offs between power generation and flood risk. This study establishes an analytical framework to derive optimal hedging rules (OHR) and explains the economic insights into flood risk reduction and power generation improvement. A two-stage model based on the concept of dynamic control of carryover storage (DCCS) was developed as part of the framework, considering forecast uncertainty and risk tolerance. The results illustrated that hedging and trade-offs between power generation and flood risk during DCCS only occurs when the forecasted inflow and forecast uncertainty are within certain ranges, beyond which there is no hedging and trade-offs analysis; either power generation or flood risk becomes the dominant objective. The OHR was divided into three cases under different levels of forecast uncertainty and risk tolerance. Compared to forecast uncertainty, downstream risk tolerance plays a more important role in determining which case of the OHR is adopted in real-world operations. The analysis revealed what and how intense trade-offs are between power generation and flood risk under different scenarios of forecasted inflow, forecast uncertainty, and risk tolerance. The framework serves as a guideline for less abundant water resources or energy-stressed areas of operational policy. Nierji Reservoir (located in northeast China) was taken as a case study to illustrate the analysis, and the application results showed that OHR increases the average annual power generation by 4.09% without extra flood risk compared to current operation rules. [ABSTRACT FROM AUTHOR]

Hydrological processes regulate the ecological processes of a basin. Climate change and anthropological activities lead to changes in the natural hydrological process of rivers, whereas variations in hydrological processes can disrupt the stability of ecosystems, resulting in various ecological challenges. Quantitative evaluation of ecological water demand and its key components can play a key role in the sustainable development of ecosystems. The studies of ecohydrological variation and multi-objective ecological water demand are of great significance for ecological protection and remediation due to the unique characteristics of each river basin and diverse ecological protection objectives. This study identified ecohydrological variation in ecosystems, focusing on the Irtysh River Basin as a case study, and improved methods for ecological water demand of valley forests and grasslands in terrestrial ecosystems and for the ecological water level of lake ecosystems. The results demonstrated that: (1) a drastic decrease in the annual average river flow of the basin and significant changes in ecohydrological characteristics can lead to reduced biomass; (2) the ecological water demand of valley forests and grasslands during the critical ecological stage (April–September) was 521 million m³, with 52.4% of total demand occurring in June and July. The minimum ecological water levels of the Burultokay and Jili lakes were 478.66 m and 480.66 m, whereas the maximum levels were 482.80 m and 483.20 m, respectively; (3) ecological regulation based on catchwork irrigation technology can create hydrological processes that meet the water demands of valley forests and grasslands and achieve remediation of the terrestrial ecosystem. The ecological water levels and the ecosystem balance of the Burultokay and Jili lakes can be maintained by optimizing the replenishment flow from the Irtysh River to the Burultokay Lake under different precipitation levels. This study can act as a reference for the ecological protection and remediation of the Irtysh River Basin and similar ecosystems globally. [ABSTRACT FROM AUTHOR]

Activity recognition is fundamental to many applications envisaged in pervasive computing, especially in smart environments where the resident's data collected from sensors will be mapped to human activities. Previous research usually focuses on scripted or pre-segmented sequences related to activities, whereas many real-world deployments require information about the ongoing activities in real time. In this paper, we propose an online activity recognition model on streaming sensor data that incorporates the spatio-temporal correlation-based dynamic segmentation method and the stigmergy-based emergent modeling method to recognize activities when new sensor events are recorded. The dynamic segmentation approach integrating sensor correlation and time correlation judges whether two consecutive sensor events belong to the same window or not, avoiding events from very different functional areas or with a long time interval in the same window, thus obtaining the segmented window for every single event. Then, the emergent paradigm with marker-based stigmergy is adopted to build activity features that are explicitly represented as a directed weighted network to define the context for the last sensor event in this window, which does not need sophisticated domain knowledge. We validate the proposed method utilizing the real-world dataset Aruba from the CASAS project and the results show the effectiveness. [ABSTRACT FROM AUTHOR]

Long distance water diversion projects are developed to alleviate the conflicts between supply and demand of water resources across different watersheds. However, the significant scale water diversion projects bring new challenges for the water supply security. This paper presents the flood risk of inverted siphon structure which is used for crossing transversally in the water diversion project through sensitivity analysis. Sobol and regionalized sensitivity analysis are used to investigate the sensitive parameters of the integrated model and the sensitive range of the parameters, respectively. The integrated system model consists of the hydrologic model, the sediment transport model and the siphon hydraulic model to determine the flood overtopping duration and volume, which are used to quantify flood risk in this study. The flood overtopping duration and volume indicators are used to quantify flood risk in the sensitivity analysis. The South to North Water Diversion Project in China is used as a case study. The results show the mean rainfall and roughness coefficient of the pipe are the most sensitive parameters in the integrated models, while the sensitive range of these two parameters are distinct. The sensitivity analysis of the inverted siphon provides an insight into the significant contributions to the flood risk. The analysis can provide the guidance for the system operation security. [ABSTRACT FROM AUTHOR]

The SQUAMOSA-PROMOTER BINDING PROTEIN-LIKE (SPL) gene family affects plant architecture, panicle structure, and grain development, representing key genes for crop improvements. The objective of the present study is to utilize the well characterized SPLs' functions in rice to facilitate the functional genomics of TaSPL genes. To achieve these goals, we combined several approaches, including genome-wide analysis of TaSPLs, comparative genomic analysis, expression profiling, and functional study of TaSPL3 in rice. We established the orthologous relationships of 56 TaSPL genes with the corresponding OsSPLs, laying a foundation for the comparison of known SPL functions between wheat and rice. Some TaSPLs exhibited different spatial–temporal expression patterns when compared to their rice orthologs, thus implicating functional divergence. TaSPL2/6/8/10 were identified to respond to different abiotic stresses through the combination of RNA-seq and qPCR expression analysis. Additionally, ectopic expression of TaSPL3 in rice promotes heading dates, affects leaf and stem development, and leads to smaller panicles and decreased yields per panicle. In conclusion, our work provides useful information toward cataloging of the functions of TaSPLs, emphasized the conservation and divergence between TaSPLs and OsSPLs, and identified the important SPL genes for wheat improvement. [ABSTRACT FROM AUTHOR]

Bacterial canker caused by Pseudomonas syringae pv. actinidiae (Psa) has led to considerable losses in all major kiwifruit-growing areas. There are no commercial products in the market to effectively control this disease. Therefore, the defense resistance of host plants is a prospective option. In our previous study, sulfur could improve the resistance of kiwifruit to Psa infection. However, the mechanisms of inducing resistance remain largely unclear. In this study, disease severity and protection efficiency were tested after applying sulfur, with different concentrations in the field. The results indicated that sulfur could reduce the disease index by 30.26 and 31.6 and recorded high protection efficiency of 76.67% and 77.00% after one and two years, respectively, when the concentration of induction treatments was 2.0 kg/m3. Ultrastructural changes in kiwifruit stems after induction were demonstrated by scanning electron microscopy (SEM) and transmission electron microscopy (TEM), and the activities of phenylalanine ammonia-lyase (PAL), peroxidase (POD) and polyphenol oxidase (PPO), and the accumulation of lignin were determined by biochemical analyses. Our results showed that the morphological characteristics of trichomes and lenticels of kiwifruit stem were in the best defensive state respectively when the sulfur concentration was 3.0 kg/m3 and 1.5 kg/m3. Meanwhile, in the range of 0.5 to 2.0 kg/m3, the sulfur could promote the chloroplast and mitochondria of kiwifruit stems infected with Psa to gradually return to health status, increasing the thickness of the cell wall. In addition, sulfur increased the activities of PAL, POD and PPO, and promoted the accumulation of lignin in kiwifruit stems. Moreover, the sulfur protection efficiency was positively correlated with PPO activity (p < 0.05) and lignin content (p < 0.01), which revealed that the synergistic effect of protective enzyme activity and the phenolic metabolism pathway was the physiological effect of sulfur-induced kiwifruit resistance to Psa. This evidence highlights the importance of lignin content in kiwifruit stems as a defense mechanism in sulfur-induced resistance. These results suggest that sulfur enhances kiwifruit canker resistance via an increase in phenolic components and morphology structure modification in the kiwifruit stems. Therefore, this study could provide insights into sulfur to control kiwifruit canker caused by Psa. [ABSTRACT FROM AUTHOR]

The crucial function of the internal transcribed spacer 2 (ITS2) region in ribosome biogenesis depends on its secondary and tertiary structures. Despite rapidly evolving, ITS2 is under evolutionary constraints to maintain the specific secondary structures that provide functionality. A link between function, structure and evolution could contribute an understanding to each other and recently has created a growing point of sequence-structure phylogeny of ITS2. Here we briefly review the current knowledge of ITS2 processing in ribosome biogenesis, focusing on the conservative characteristics of ITS2 secondary structure, including structure form, structural motifs, cleavage sites, and base-pair interactions. We then review the phylogenetic implications and applications of this structure information, including structure-guiding sequence alignment, base-pair mutation model, and species distinguishing. We give the rationale for why incorporating structure information into tree construction could improve reliability and accuracy, and some perspectives of bioinformatics coding that allow for a meaningful evolutionary character to be extracted. In sum, this review of the integration of function, structure and evolution of ITS2 will expand the traditional sequence-based ITS2 phylogeny and thus contributes to the tree of life. The generality of ITS2 characteristics may also inspire phylogenetic use of other similar structural regions. [ABSTRACT FROM AUTHOR]

Radio tomographic imaging (RTI) is a technology for target localization by using radio frequency (RF) sensors in a wireless network. The change of the attenuation field caused by the target is represented by a shadowing image, which is then used to estimate the target's position. The shadowing image can be reconstructed from the variation of the received signal strength (RSS) in the wireless network. However, due to the interference from multi-path fading, not all the RSS variations are reliable. If the unreliable RSS variations are used for image reconstruction, some artifacts will appear in the shadowing image, which may cause the target's position being wrongly estimated. Due to the sparse property of the shadowing image, sparse Bayesian learning (SBL) can be employed for signal reconstruction. Aiming at enhancing the robustness to multipath fading, this paper explores the Laplace prior to characterize the shadowing image under the framework of SBL. Bayesian modeling, Bayesian inference and the fast algorithm are presented to achieve the maximum-a-posterior (MAP) solution. Finally, imaging, localization and tracking experiments from three different scenarios are conducted to validate the robustness to multipath fading. Meanwhile, the improved computational efficiency of using Laplace prior is validated in the localization-time experiment as well. [ABSTRACT FROM AUTHOR]

Climate change is affecting the discharge of headstreams from mountainous areas on the Qinghai–Tibet Plateau. To constrain future changes in discharge, it is important to understand the present-day formation mechanism and components of runoff in the basin. Here we explore the sources of runoff and spatial variations in discharge through measurements of δ2H and δ18O in the Naqu River, at the source of the Nu River, on the Qinghai–Tibet plateau, during the month of August from 2016 to 2018. We established thirteen sampling sites on the main stream and tributaries, and collected 39 samples from the river. We examined all the water samples and analyzed them for isotopes. We find a significant spatial variation trend based on one-way analysis of variance (ANOVA) (p < 0.05) between Main stream-2 and tributaries. The local meteoric water-line (LMWL) can be described as: δ2H = 7.9δ18O + 6.29. Isotopic evaporative fractionation in water and mixing of different water sources are responsible for the spatial difference in isotopic values between Main stream-2 and tributaries. Based on isotopic hydrograph separation, the proportion of snowmelt in runoff components ranges from 15% to 47%, and the proportion of rainwater ranges from 3% to 35%. Thus, the main components of runoff in the Naqu River are snowmelt and groundwater. [ABSTRACT FROM AUTHOR]

Lakes are important for global ecological balance and provide rich biological and social resources. However, lake systems are sensitive to climate change and anthropogenic activities. Poyang Lake is an important wetland in the middle reach of the Yangtze River, China and has a complicated interaction with the Yangtze River. In recent years, the water level of Poyang Lake was altered dramatically, in particular showing a significant downward trend after the operation of the Three Gorges Dam (TGD) in 2003, thus seriously affecting the lake wetland ecosystem. The operation of the TGD changed both the hydrological regime and the deeper channel in the middle reach of the Yangtze River, and affected the river–lake system between the Yangtze River and Poyang Lake. This study analyzed the change in the water level of Poyang Lake and quantified the contributions of the TGD operation, from the perspectives of water storage and erosion of the deeper channel in the middle reach of the Yangtze River, through hydrodynamic model simulation. The erosion of the deeper channel indicated a significant decrease in annual water level. However, due to the water storage of the TGD in September and October, the discharge in the Yangtze River sharply decreased and the water level of Poyang Lake was largely affected. Especially in late September, early October, and mid-October, the contributions of water storage of the TGD to the decline in the water level of Poyang Lake respectively reached 68.85%, 59.04%, and 54.88%, indicating that the water storage of the TGD was the main factor in the decrease in water level. The erosion of the deeper channel accelerated the decline of the water level of Poyang Lake and led to about 10% to 20% of the decline of water level in September and October. Due to the combined operation of the TGD and more reservoirs under construction in the upper TGD, the long-term and irreversible influence of the TGD on Poyang Lake should be further explored in the future. [ABSTRACT FROM AUTHOR]

Device-Free Localization (DFL) based on the Radio Frequency (RF) is an emerging wireless sensing technology to perceive the position information of the target. To realize the real-time DFL with lower power, Back-projection Radio Tomographic Imaging (BRTI) has been used as a lightweight method to achieve the goal. However, the multipath noise in the RF sensing network may interfere with the measurement and the BRTI reconstruction performance. To resist the multipath interference in the observed data, it is necessary to recognize the informative RF link measurements that are truly affected by the target appearance. However, the existing methods based on the RF link state analysis are limited by the complex distribution of the RF link state and the high time complexity. In this paper, to enhance the performance of RF link state analysis, the RF link state analysis is transformed into a decomposition problem of the RF link state matrix, and an efficient RF link recognition method based on the low-rank and sparse decomposition is proposed to sense the spatiotemporal variation of the RF link state and accurately figure out the target-affected RF links. From the experimental results, the RF links recognized by the proposed method effectively reflect the target-induced RSS measurement variation with less time. Besides, the proposed method by recognizing the informative measurement is helpful to improve the accuracy of BRTI and enhance the efficiency in actual DFL applications. [ABSTRACT FROM AUTHOR]

The stable isotopic study of the mechanism of runoff replenishment in the Qinghai-Tibet Plateau is a time-consuming and complicated process requiring complex monitoring data and scientific evaluation methods. Based on the data of water stable isotopes (18O and 2H) in the Naqu River basin, the present paper developed a framework of the variable fuzzy evaluation model (VFEM) to provide a method to classify stable isotopes and generalize the source identification of water replenishment by rainfall or snowmelt in the Naqu River basin. The grade eigenvalues of tributaries were ranked from low to high as follows: 1, 1.005, 1.089, 1.151, 1.264, 1.455 and 2.624. Three sets of tributaries were distinguished. The grade eigenvalues of the Najinqu, Bazongqu, Mumuqu, Chengqu and Gongqu Rivers were small, indicating that these tributaries were strongly supplemented by precipitation and snowmelt; the grade eigenvalue of the Zongqingqu River was in the medium range (1.455); the third group included the Mugequ River with a high status value (2.624). This study mainly highlighted the combination of the classification of stable isotopes and plots of δ2H vs. δ18O in the source identification of water replenishment, which will be helpful for studying runoff replenishment and the evolution mechanism in the Qinghai-Tibet Plateau. [ABSTRACT FROM AUTHOR]

The relationship among the lysyl oxidase (LOX) G473A single nucleotide polymorphism (SNP), cigarette smoking and lung, colorectal, colon and rectum cancer susceptibility was studied in 200 cases of lung cancer, 335 cases of colorectal cancer including 130 cases of colon cancer and 205 cases of rectum cancer, and 335 healthy people in Tangshan, China. Peripheral blood DNA samples were collected, DNA sequencing and polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) performed, followed by multivariate logistic regression analysis. In comparison to LOX473GG genotype carriers, individuals with LOX473AA exhibited a higher susceptibility to lung, colon-rectum, colon, and rectum cancers with OR values amounting to 3.84-, 2.74-, 2.75-, and 2.74-fold of the control, respectively. In the LOX 473AA-positive population, females were more susceptible than males to carcinogenesis with OR values (female vs. male): 5.25 vs. 3.23, 2.29 vs. 1.51, 2.27 vs. 1.45, and 2.25 vs. 1.53, respectively, for lung, colon-rectum combined, colon, and rectum cancers. LOX G473A polymorphism apparently elevated human sensitivity to cigarette smoking carcinogens for eliciting cancers in the lung and colon only. Thus, LOX G473A polymorphism positively correlates with carcinogenesis and it may be used as an ideal intrinsic biomarker for prediction or diagnosis of carcinogenesis in humans.