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Tilia species are valuable woody species due to their beautiful shape and role as honey trees. Somatic embryogenesis can be an alternative method for mass propagation of T. amurensis . However, the molecular mechanisms of T. amurensis somatic embryogenesis are yet to be known. Here, we conducted comparative transcriptional analysis during somatic embryogenesis of T. amurensis . RNA-Seq identified 1505 differentially expressed genes, including developmental regulatory genes. Auxin related genes such as YUC, AUX/IAA and ARF and signal transduction pathway related genes including LEA and SERK were differentially regulated during somatic embryogenesis. Also, B3 domain family ( LEC2, FUS3), VAL and PKL, the regulatory transcription factors, were differentially expressed by somatic embryo developmental stages. Our results could provide plausible pathway of signaling somatic embryogenesis of T. amurensis , and serve an important resource for further studies in direct somatic embryogenesis in woody plants.

The Hibiscus genus of the Malvaceae family is widely distributed and has diverse applications. Hibiscus sinosyriacus is a valuable ornamental tree, but it has not been extensively researched. This study aimed to complete the chloroplast genome of H. sinosyriacus and elucidate its evolutionary relationship with closely related species and genera. The complete chloroplast genome of H. sinosyriacus was found to be 160,892 bp in length, with annotations identifying 130 genes, including 85 coding genes, 37 tRNAs, and 8 rRNAs. Interspecific variations in the Hibiscus spp. were explored, and H. sinosyriacus has species-specific single-nucleotide polymorphisms in four genes. Genome structure analysis and visualization revealed that in the Abelmoschus genus, parts of the large single-copy region, including rps19, rpl22, and rps3, have been incorporated into the inverted repeat region, leading to a duplication and an increase in the number of genes. Furthermore, within the Malvales order, the infA gene remains in some genera. Phylogenetic analysis using the whole genome and coding sequences established the phylogenetic position of H. sinosyriacus. This research has further advanced the understanding of the phylogenetic relationships of Hibiscus spp. and related genera, and the results of the structural and variation studies will be helpful for future research.

Hibiscus trionum L. is an annual herbaceous plant belonging to the Malvaceae family. It is native to Central Africa, however, is now naturalized in Europe and Asia including Korea. Here, we report the complete chloroplast genome assembly of H. trionum. The complete chloroplast genome comprises 160,530 bp and is divided into four typical regions: a large single-copy region of 89,272 bp, a pair of inverse repeats of 26,152 bp each, and a small single-copy region of 18,954 bp. A total of 131 genes were identified in this chloroplast, of which 86 were protein-coding, 37 were tRNA, and 8 were rRNA genes. The results of this study will serve as a key reference for further research on Hibiscus speciation.

Blume 1851, an evergreen broad-leaved species belonging to the family Fagaceae, is primarily distributed from southern Korea to Japan. In this study, we comprehensively analyzed the chloroplast genome of . Its genome, with a quadripartite structure, spanned 160,801 bp and had a GC content of 36.58%. Annotation revealed 131 genes, including 86 protein-coding genes, eight rRNA genes, and 37 tRNA genes. These intricacies in the genome were further confirmed by the presence of introns in multiple genes. Phylogenetic analysis of 19 Fagales species elucidated their evolutionary relationships, with branching early and showing a close relationship with . This study enhances our understanding of the genetic makeup of and its evolutionary dynamics within the .

As the national flower of Korea, the Hibiscus syriacus L. (Rose of Sharon) is symbolic in its abundance and is a prominent feature of Korean culture. H. syriacus has played an important role in Korea, not only as an ornamental plant but also as an essential ingredient in folk remedies through its various parts. This study aimed to characterize the nutritional and biochemical composition of each plant unit of H. syriacus “Wonhwa.” The units are namely: the petals, leaves, roots, and sprouts from its seeds. According to the results each unit produced, the sprouts had the highest content of amino acids and fatty acids which adhere to the requirements of nutritionally excellent food ingredients. The petals produced high quantities of glucose, sucrose, and fumaric acid, with the highest antioxidant activity among the four units. The main bioactive compounds detected in H. syriacus extracts in the four units were o‐coumaric acid, p‐coumaric acid, schaftoside, isoschaftoside, apigenin‐6‐C‐glucoside‐7‐o‐glucoside, and kaempferol‐3‐O‐galactoside‐7‐O‐rhamnoside. Overall, the highest number of bioactive compounds, 2 phenolic acids and 22 flavonoids, were identified in the petals. These results suggest the possibility of excellent pharmacological activity in the petals. This study was carried out with the intention of identifying benefits for human consumption of H. syriacus in terms of their individual units, as well as to detect other functional attributes of the components. To conclude, the results generated in this study strongly suggest the possibility of excellent pharmacological activity and nutritional advantages of not only the petals but across each division of the H. syriacus plant.

The coordinate transformation method of asymmetric dual three phase synchronous motor (ADTP-SM) is a Double dq transform using two dq-axes and a vector space decomposition (VSD) model method using the orthogonality of ADTP-SM. There are several studies comparing the two methods in a healthy state, but few in a single-phase open fault state. In the healthy, when the VSD model is applied, different harmonic orders of the phase current are projected onto the dq and xy-axes (the axis for controlling harmonics of the phase current), and the two-axes are orthogonal, so it can be controlled stably. In the single-phase open fault state, the same current control logic as in the healthy situation is applied. When applying the Double dq transform, the dq-axis of the fault set fluctuates, and it affects the healthy set, so it cannot be controlled stably. When applying the VSD model, if both the dq-axis and the xy-axis are controlled, the two coordinate systems do not have orthogonality and cannot be stably controlled, due to mutual interference. However, if only the dq-axis is controlled, it can be controlled stably because there is no Cartesian coordinate system other than the dq-axis. In the healthy state and single-phase open fault state, the equation is verified through experiments and simulations, and the control stability according to the coordinate transformation is compared.

Designing an effective isolation valve system (IVS) is vital to enhance resilience against unforeseen failures in water systems. During isolation, the system’s hydraulics undergo changes, potentially causing alterations in flow direction and velocity, leading to the dislodgement of accumulated materials and triggering unexpected water quality incidents. This study presents a novel IVS design approach by integrating the consideration of flow direction change (FDC) as an additional constraint within conventional reliability-based models. Two optimization models, Optimization I and Optimization II, prioritize reliability, with the latter also factoring in valve installation cost as a multi-objective function. Performance evaluation metrics, such as the Hydraulic Geodesic Index (HGI), Modified Resilience Index (MRI), and robustness index, were employed for a comprehensive analysis. The results indicated more than 40 instances of FDC in the traditional design, challenging the conventional notion that a higher number of valves inherently reduces risk. The superiority of the proposed model persisted for the single reservoir network in Optimization II. However, for networks with multiple reservoirs, the traditional design outperformed the proposed model, particularly in terms of cost. Nevertheless, when comparing designs with similar reliability, the proposed model showcased a superior performance, despite its higher associated cost. Notably, the proposed approach exhibits potential cost-effectiveness, considering the potential economic losses attributable to water quality incidents. In summary, the implementation of this methodology can effectively manage both water quality and quantity, enabling the identification of vulnerable pipes within the network for sustainable management.

In the last decade, machine learning (ML) technology has been transforming daily lives, industries, and various scientific/engineering disciplines. In particular, ML technology has resulted in significant progress in neural network models; these enable the automatic computation of problem-relevant features and rapid capture of highly complex data distributions. We believe that ML approaches can address several significant new and/or old challenges in urban drainage systems (UDSs). This review paper provides a state-of-the-art review of ML-based UDS modeling/application based on three categories: (1) operation (real-time operation control), (2) management (flood-inundation prediction) and (3) maintenance (pipe defect detection). The review reveals that ML is utilized extensively in UDSs to advance model performance and efficiency, extract complex data distribution patterns, and obtain scientific/engineering insights. Additionally, some potential issues and future directions are recommended for three research topics defined in this study to extend UDS modeling/applications based on ML technology. Furthermore, it is suggested that ML technology can promote developments in UDSs. The new paradigm of ML-based UDS modeling/applications summarized here is in its early stages and should be considered in future studies.

Urban drainage systems (UDSs) continue to face challenges, despite numerous efforts to improve their sustainability through design, planning, and management. The goal of such initiatives is to avoid and minimize flooding as well as maintain the UDS’s sustainable functionality, which can be analyzed using a stormwater management model (SWMM). In this study, a multiobjective automatic parameter-calibration (MAPC) framework was developed based on the SWMM. It consisted of three steps: sensitivity analysis (Step I), objective selection (Step II), and SWMM parameter calibration (Step III). The proposed MAPC framework was verified using the Yongdap drainage network located in Seoul, South Korea. The resultant MAPC framework demonstrated that the system characteristics (such as percent of impervious area and hillslope) and problems in UDS design, planning, and management can be well reflected by the corresponding model. The MAPC framework proposed in this study can contribute to UDS modeling sustainability.

Global climate change exacerbates urban floods, making their projection into future uncertainties more challenging. Identifying flood impact factors in urban areas is necessary for effective urban flood risk management. However, studies investigating the priority determination among flood impact factors based on an integrated decision‐making tool are limited. This study proposes an integrated flood risk matrix combining two methods. The proposed tool comprises quantitative and qualitative approaches to comprehensively investigate the priorities among flood impact factors. The quantitative approach examines the “uncertainty,” and the qualitative approach investigates the “importance”. The proposed tool, combined with two measures, performs priority determination with respect to hydrological and hydraulic flood risk factors. Pipe roughness and curve number were identified as the key drivers (i.e., high priority). In addition, the proposed matrix demonstrated how priority determination among flood impact factors can help improve decision‐making for urban infrastructure projects. This study improves knowledge of project decision‐making by providing a mechanism that integrates two different methods while providing reliable results.