Search Results (30,989)

The accumulated ammonia within the recirculating aquaculture systems threaten fish health, while little is known about the influences during early fish ontogeny. Using larval and juvenile yellow catfish (Pelteobagrus fulvidraco) as a model, a comprehensive experiment exposing fish to varying total ammonia nitrogen concentrations (0, 10, 20 mg/L for larvae; 0, 25, 125 mg/L for juveniles) was conducted to evaluate the effects on gill transcriptome and microbiota along with the serotonergic regulation. First, the serotonin (5-HT) signal, which controls oxygen chemoreception and ventilation, was mainly detected in the surface of the body of the larvae, and then shifted to gill filaments of juveniles, showing a transition from cutaneous to branchial respiration. Both larval and juvenile yellow catfish exhibited reduced survival, damaged gill structure, and elevated 5-HT expression after ammonia exposure, as well as upregulated tph1b, slc6a4b, scgn and lama5 expression with the increased ammonia concentration, indicating the effects on respiratory function via serotonergic regulation. Further transcriptome analysis was conducted in juveniles to identify the differentially expressed genes (DEGs) and thus, to illustrate more detailed responses after ammonia exposure; KEGG enrichment analysis of DEGs indicated the coping strategy shifted from metabolic buffering to metabolic elimination via glutamine synthesis with the increased ammonia level. The qRT-PCR experiment also identified the increased expression of genes involved in the urea cycle—such as ass1, asl and glula—with the increased ammonia level. Considering the potential contributary role of microbiome to gill health, 16S sequencing was conducted on the gill in the control and the 125 mg/L ammonia-exposed group. Ammonia exposure at 125 mg/L induced significant variation in Simpson index and a marked decline in β diversity. Notably, the abundance of opportunistic pathogens such as Pseudomonadota increased, while the abundance of Deinococcota and Deinococcus—which were renowned for exceptional stress resistance capacity—decreased after ammonia exposure. Thus ammonia exposure disrupts the transcriptomic and microecological balance within gill mucosa, which may elevate the risk of pathogenic infection. Overall, our study provided the first evidence of serotonergic regulation on early fish respiration during ammonia exposure, and also offered new theoretical insights into the involvement of microorganisms in ammonia toxicity. Full article

Optimizing nitrogen form under drip fertigation may improve wheat productivity by regulating the root-zone inorganic N environment during early vegetative growth. A two-year field experiment evaluated nitrate-dominant (N1), balanced ammonium–nitrate (N2), and ammonium-enriched nitrogen strategies (N3) during GS13–GS31, with conventional farmer practice (CK) and a zero-N control (N0) for comparison. Nitrogen-form regulation markedly altered the soil NH₄⁺-N ratios, especially in the 0–20 cm soil layer, with N3 highest, N1 lowest, and N2 intermediate. Compared with the nitrate- or ammonium-dominant strategy, the balanced treatment N2 improved spike formation rate and maintained relatively higher N accumulation at GS31 and GS65, and showed greater N translocation and contribution of translocated N to grain N than N1. Correlation analyses indicated that spike formation rate was closely related to spike number (R² = 0.764) and N accumulation at GS31 was positively related to Ntrans (R² = 0.588). N2 showed the most favorable overall performance, with the highest numerical values for grain yield, nitrogen recovery efficiency, irrigation water use efficiency, and net profit among the fertigation treatments. However, the advantages of N2 over N3 in grain yield and SPAD-AUC were modest and not consistently significant. These results indicate that balancing ammonium and nitrate supply during GS13–GS31 under drip fertigation can improve root-zone N conditions and support better overall agronomic performance in winter wheat under the alkaline soil conditions of the North China Plain. Full article

Sulfur-mediated autotrophic denitrification (SAD) is an innovative and sustainable water treatment technology, which operates without an external carbon source and achieves lower sludge production. Firstly, this review provides a detailed examination of sulfur-based fillers, encompassing their respective types, preparation methods, advantages and drawbacks. Subsequently, it reviews the mainstream functional microbial communities across various process stages, such as Thiobacillus, Sulfurimonas, and Ignavibacterium. Moreover, the process characteristics of mainstream SAD reactor types, such as fluidized bed, fixed bed, and moving bed biofilm reactors, are reviewed, and the effects of key process parameters like pH, temperature, and dissolved oxygen on treatment efficiencies are further analyzed. Additionally, the applications cases of SAD in advanced wastewater treatment, river remediation, wetland restoration, and groundwater purification are summarized, demonstrating its broad and diverse application potential in environmental engineering. Finally, key challenges of SAD are identified, including the complexity of microbial metabolic interactions, the accumulation of intermediate products, and the need for improved fillers and reactor configurations. Future research priorities are discussed in three areas: microbial community regulation, control and utilization of intermediate products, and development of advanced fillers and reactor configurations. Overall, this review integrates key technical parameters and operational experience of SAD, providing a consolidated reference for researchers and practitioners interested in the development and application of this technology. Full article

In this paper, based on the Caputo-like delta fractional difference operator, we will present a fractional discrete model of a 4D Power System. We present an extension of the popular integer-order single-machine infinite-bus formulation to two fractional cases, one with commensurate (equal) fractional orders and another incommensurate (not equal). This extension captures long-memory effects in dynamics and thus offers a consistent mathematical description of the nonlinear behavior of power systems. The orders of the fractional models are analyzed numerically. Using time series evolution, phase-space plots, bifurcation maps, Lyapunov spectra, and the 0–1 chaos test, spectral entropy and $C_0$ complexity metrics, we identify chaotic regimes. Additionally, techniques for controlling chaos are explored to stabilize and regulate the dynamics of the system. Both the fractional formulations exhibit richer dynamical features than their integer counterparts, and for the incommensurate case, the sensitivity to the fractional variations is larger, generating complex nonlinear oscillations. The fractional discrete power system framework provides a new perspective for studying instability, the voltage collapse phenomenon, and chaotic oscillations in power engineering applications. Full article

The accelerated low-carbon transition of power systems and the widespread integration of Electric Vehicles (EVs) present both severe operational challenges and substantial flexible regulation potential for Active Distribution Networks (ADNs). This paper provides an integrative review of the coordinated control and multi-market bidding mechanisms for EV-centric Technical Virtual Power Plants (TVPPs). Moving beyond descriptive surveys, this review systematically synthesizes the fragmented literature across three critical dimensions: (1) the physical-economic bidirectional mapping, which considers nonlinear power flow constraints and node voltage limits within the TVPP framework; (2) multi-market coupling mechanisms, evolving from unilateral energy bidding to coordinated participation in carbon trading and ancillary services; and (3) real-time control strategies, critically evaluating the trade-offs between optimization techniques (e.g., Model Predictive Control) and cutting-edge artificial intelligence approaches (e.g., Deep Reinforcement Learning) in mitigating battery degradation. Furthermore, a transparent review methodology is adopted to ensure literature rigor. By explicitly outlining the boundaries between TVPPs, Commercial VPPs (CVPPs), and EV aggregators, this paper identifies core unresolved trade-offs among aggregation fidelity, market complexity, and communication latency, providing evidence-backed pathways for future engineering demonstrations and V2G applications. Full article

The cigarette beetle, Lasioderma serricorne, is a globally important pest of stored products, and prolonged fumigant use has accelerated resistance development. Glutathione S-transferases (GSTs) are key phase II detoxification enzymes that mediate insect tolerance to xenobiotics. In this study, we identified nine GST genes (LsGSTs) in L. serricorne and classified them into four cytosolic classes, namely epsilon, delta, theta, and sigma, based on phylogenetic analysis. Most LsGSTs were predominantly expressed during larval stages, while LsGSTs7 showed peak expression in adults. Tissue-specific profiling revealed predominant expression in metabolically active organs, including the fat body, Malpighian tubules, and midgut. Inhibition of GST activity using diethyl maleate (DEM) significantly increased larval susceptibility to three emerging fumigants: ethyl formate, benzothiazole, and methyl isothiocyanate. Exposure to LC₃₀ and LC₅₀ concentrations of these fumigants induced up-regulation of multiple LsGSTs, highlighting fumigant-specific detoxification responses. RNA interference targeting nine fumigant-inducible LsGSTs markedly elevated mortality and decreased total GST activity under fumigant stress. Furthermore, recombinant LsGSTs6 protein effectively metabolized methyl isothiocyanate, confirming their direct role in fumigant detoxification. Collectively, these findings provide novel insights into the molecular mechanisms underlying GST-mediated tolerance in L. serricorne and identify specific GST isoenzymes as promising molecular targets for innovative resistance management strategies in stored-product pest control. Full article

Generally, forest trees with medicinal value present diverse chemotypes considered key determinants of efficacy, safety, and commercial valuation. Such heterogeneity varies among tissues, genotypes, and seasons, and stress exposure. This review summarizes how regulatory controls and genome architecture affect the stability and synthesis of secondary metabolites in woody medicinally important taxa. Detailed haplotypic and chromosomal analyses have recently identified diverse and repeatable architectural drivers. Among these, LTR/transposon-mediated revamping, neofunctionalization, biosynthetic gene clusters, and tandem duplication play a special role in reshaping pathway capacity. The enzymatic regulation of these drivers translates this “capacity” into harvest-pertinent chemistry by employing conserved TF modules, hormone crosstalk, and emergent chromatin/epigenetic layers. Nevertheless, major parameters pertaining to the tissue-specific storage, transport, and compartmentalization of these chemotypes are contextualized with certain limitations. In this review, the integration of GWAS/eQTL/TWAS with multi-tissue is explained in addition to the replacement of a single reference with pangenome/haplotype frameworks, and explicit modeling of G × E further strengthen genotype-to-chemotype mapping. Therefore, in this review we summarize practical workflows for chemotype discovery utilizing staged validation models of heterologous reconstitution, isotope/spatial evidence, and chemistry. These findings were supported by data on saponins, alkaloids, iridoids, and defense response. Such an integration links mechanistic understanding to authentication, standardization, and sustainable utilization strategies in woody medicinal trees. Full article

To mitigate low-speed speed oscillations in permanent magnet synchronous motors (PMSMs) arising from the combined effects of rotor-position-related periodic disturbances and external perturbations, this paper develops a composite robust speed regulation scheme that integrates non-singular terminal sliding mode control (NTSMC) with angle-domain iterative learning control (ILC). First, a non-singular terminal sliding mode speed controller is established to remove the singularity inherent in conventional terminal sliding mode formulations while preserving finite-time error convergence. To further improve robustness and reduce chattering, an enhanced generalized super-twisting reaching law incorporating a continuous saturation function is introduced. Second, to compensate for periodic disturbances associated with rotor position, an angle-domain ILC law is constructed to iteratively learn the periodic speed-tracking error, thereby suppressing low-speed speed ripple. Meanwhile, an extended state observer (ESO) is incorporated to estimate aperiodic disturbances online, enabling coordinated rejection of disturbances with different temporal characteristics. Experimental results demonstrate that the proposed composite strategy effectively weakens the dominant harmonic components in speed fluctuation and enhances low-speed operational smoothness, confirming the effectiveness of the developed method. Full article

Sweet–waxy maize is a highly valuable specialty maize type with an increasing market demand, but conventional breeding methods for producing sweet–waxy maize are restricted by severe bottlenecks, such as long breeding cycles and linkage drag. This study was conducted to rapidly create sweet–waxy maize germplasm using CRISPR/Cas9 genome-editing technology. We used a CRISPR/Cas9 system to target maize Sh2 (regulating the super-sweet kernel trait) and Wx (controlling the waxy kernel trait), which are two key genes in the starch biosynthesis pathway. Two small-guide RNAs (sgRNAs) designed for each gene were incorporated into CRISPR/Cas9 vectors, which were then introduced into maize via Agrobacterium-mediated transformation. We obtained Cas9-free T₃ homozygous sh2 and wx mutant lines with significant increases in kernel soluble sugar and amylopectin contents, respectively, but no adverse changes to major agronomic traits. Using these Cas9-free lines, we developed a new type of sweet–waxy maize germplasm, in which waxy and sweet kernels on the same ear segregated at a 3:1 ratio. Our results indicate that CRISPR/Cas9-mediated editing of Sh2 and Wx can efficiently generate sweet–waxy maize germplasm with no detectable linkage drag. The study methods would be useful for optimizing the molecular breeding of novel and innovative maize germplasm. Full article

Leaf senescence, the final developmental stage of a leaf, is a highly regulated process that is vital for the recycling of nutrients and the maintenance of plant fitness. Its control operates at multiple levels, including chromatin remodeling, transcription, post-transcriptional regulation, translation, and post-translational modifications. This review summarizes recent advances in understanding the roles of key transcription factor (TF) families—WRKY, NAC, and MYB—in modulating leaf senescence in Arabidopsis thaliana. We detail how these TFs integrate internal and external signals to regulate senescence-associated genes (SAGs). In addition, we explore the pivotal role of microRNAs (miRNAs) in post-transcriptional control of senescence, focusing on their regulation of these TF families. In conjunction with the transcriptome data of Arabidopsis miRNAs under conditions of dark-induced senescence, we also highlight several novel senescence-associated miRNAs. Integrating transcriptional and post-transcriptional perspectives, this review presents an updated regulatory network for leaf senescence and discusses potential applications for manipulating senescence in crops to improve yield and quality. Full article

Coking coal flotation is a typical nonlinear, multi-variable, and multi-objective process in which concentrate quality and combustible matter recovery must be balanced under fluctuating feed and operating conditions. To improve both predictive reliability and decision support, this study proposes an integrated data-driven framework that combines particle swarm optimization-back propagation (PSO-BP) prediction, SHapley Additive exPlanations (SHAP) based interpretation, Non-dominated Sorting Genetic Algorithm II (NSGA-II) optimization, and entropy-weighted Technique for Order Preference by Similarity to Ideal Solution (Entropy-TOPSIS) decision-making. After three-sigma outlier screening, 2000 valid distributed control system (DCS) samples were retained for model development and temporal holdout evaluation, and an additional 200 later-period industrial samples were used for independent validation. The data were partitioned chronologically, with months 1–4, month 5, and month 6 used for training, validation, and temporal holdout testing, respectively, while the months 7–8 dataset was reserved for later-period validation. The results show that PSO-BP consistently outperformed conventional BP under both temporal holdout and later-period validation. SHAP analysis identified raw coal ash and collector dosage as the dominant factors for product-quality prediction, while collector dosage and frother dosage contributed most strongly to tailing heat of combustion. NSGA-II further revealed the trade-off among clean coal ash, clean coal sulfur, and tailing heat of combustion, and Entropy-TOPSIS converted the Pareto-optimal candidate set into a practically balanced operating recommendation. Sensitivity and robustness analyses indicated acceptable stability of both the optimization process and the final decision result. Overall, the proposed framework provides an interpretable prediction–optimization–decision workflow for coking coal flotation and offers a practical basis for future DCS-assisted intelligent regulation. Full article

Flexible factories and adaptive fabrication lines offer a testbed for advanced multimodal interaction concepts that can support the inclusion of disabled workers in Industry 5.0 manufacturing systems. The study synthesizes interdisciplinary data from ergonomics, industrial automation, and EU regulatory frameworks to establish a conceptual model for human-machine interaction. Building on conceptual modeling and a structured literature analysis, the study proposes a six-step integration framework that links task demands, worker capabilities, and interaction modalities within human-in-the-loop manufacturing environments. Although no empirical case study was conducted in this phase, an exemplary application is presented for a semi-automated bike wheel manufacturing process. Detailed machine-based assembly line flows and simulated process data were utilized for illustrative purposes to depict the process and validate the proposed Capability–Task Matching Matrix. The results operationalize the human-centric vision of Industry 5.0 by providing a structured methodology for the inclusion of disabled workers within fabrication environments. The findings are organized into two primary components: the conceptual development of the Integration Approach and its practical application to a semi-automated industrial use-case. Finally, a particular focus is placed on Brain–Computer Interfaces (BCIs) as an emerging interaction channel that enables non-muscular control, attention monitoring, and neuroadaptive feedback, complementing conventional interfaces rather than replacing them. The framework is illustrated through application to the same semi-automated bicycle wheel assembly line, where BCI-supported interaction, augmented interfaces, and robotic assistance are mapped to specific production tasks and assessed in terms of feasibility and technological maturity. Drawing on the paper’s results, an explanatory 10-year roadmap outlines the feasibility and phased deployment of BCI solutions. It aligns technological advances with European regulations and a vision for a fully inclusive manufacturing enterprise. Full article

Since its discovery in higher plants, melatonin has attracted considerable attention for its antioxidant properties and its diverse roles in plant physiology and stress responses. However, its biosynthetic pathway remains only partially elucidated, particularly in horticultural crops of economic and nutritional importance, such as pepper (Capsicum annuum L.) fruits. In our previous work, we identified five genes encoding tryptophan decarboxylase (TDC), the first enzyme in the melatonin biosynthetic pathway in pepper. The present study expands on this by identifying and characterizing additional genes encoding enzymes involved in subsequent steps of the pathway, including four tryptamine 5-hydroxylase (T5H) genes, two serotonin N-acetyltransferase (SNAT) genes, three N-acetylserotonin O-methyltransferase (ASMT) genes, two caffeic acid O-methyltransferase (COMT) genes, and one N-acetylserotonin deacetylase (ASDAC) gene, representing a total of twelve newly identified genes. We further examined their expression in sweet pepper fruits and found that only nine of the identified genes are expressed in the fruit, with generally higher transcript levels during the unripe stages. Melatonin quantification in the California-type ‘Masami’ cultivar using UPLC with fluorescence detection (FD) revealed concentrations of 623 ng melatonin·g⁻¹ dry weight (DW) in green fruits and 431 ng melatonin·g⁻¹ DW in red fruits, consistent with the higher expression of melatonin biosynthetic genes in unripe fruit. Expression analysis of these genes by means of RNA-seq revealed differential modulation in response to exogenous melatonin treatments (20, 50, and 100 µM). To our knowledge, this is the first report demonstrating that exogenous melatonin regulates the expression of genes involved in its own biosynthetic pathway in sweet pepper fruits. Notably, treatment with 100 µM melatonin delayed ripening in these non-climacteric fruits, highlighting its potential biotechnological application for controlling fruit ripening and improving postharvest management. Full article

Background: Frequent nocturnal arousals are a core feature of comorbid insomnia and obstructive sleep apnea (COMISA), yet the underlying central mechanisms remain unclear. Identifying brain functional correlates of nocturnal awakenings may help clarify arousal-related mechanisms and inform potential interventional targets. Methods: A total of 99 participants (COMISA, insomnia alone, OSA alone, and healthy controls) underwent clinical assessments, polysomnography, and brain magnetic resonance imaging (MRI). MRI metrics were compared across groups, followed by correlation and regression analyses with the arousal index, adjusting for respiratory events and insomnia-related factors. Results: Patients with COMISA exhibited more severe insomnia symptoms, greater daytime dysfunction, and more frequent nocturnal awakenings than those with insomnia alone, although their arousal index did not differ from that of the OSA group. Patients with COMISA exhibited altered activity in the right cerebellar lobule VIII (Cerebelum_8_R), left middle temporal gyrus, and right inferior frontal gyrus, opercular part. Lower fractional amplitude of low-frequency fluctuations (fALFF) in the Cerebelum_8_R was associated with a higher arousal index. This association remained significant after controlling for insomnia severity and sleep efficiency but was attenuated after adjustment for AHI. Conclusions: Reduced functional activity in the Cerebelum_8_R was independently associated with sleep fragmentation in COMISA, independent of insomnia severity but potentially mediated by respiratory events. These findings suggest this region may be involved in arousal-related neural regulation and could represent a therapeutic target for the complex symptoms of COMISA. Trial Registration: Chinese Clinical Trial Registry, ChiCTR2500095809. Full article

The increasing operational variability in distribution networks (e.g., abrupt load changes and distributed generation integration) increases the demands on voltage regulation devices and, in particular, on transformers with on-load tap changers (OLTCs). This paper develops and validates a discrete supervisory control scheme based on Petri nets, implemented in Stateflow and coupled to an electromagnetic model of the OLTC transformer in Simulink/Simscape. The Petri net formalizes the conditional and sequential logic of OLTC operation, enabling state- and time-dependent decisions (e.g., delays between maneuvers) to improve voltage regulation and reduce unnecessary tap operations. The evaluation is performed by simulation under transient scenarios that include sudden load variations anda phase-to-ground fault in the IEEE 13-node standard network, specifically at node 634. In the base case, the controller maintains the voltage within the tolerance band $\pm 1.875\%$ during 96% of the simulated time, with an 88% reduction in RMS error (from 1.92% to 0.23%) and 100% operational efficiency (16 effective maneuvers, with a single hunting event). Subsequently, the scheme is validated on the standard IEEE 13-node network, with four disturbances applied over 600 s (two load increments, photovoltaic injection, and a temporary line disconnection). In this case, regulation remains within a precision zone of $\pm 0.3\%$ for 96.8% of the time, with an average RMS error of 0.23% and 100% efficiency, with no hunting events. The results confirm that a Petri net-based supervisory logic can simultaneously improve the OLTC’s voltage quality and switching efficiency, providing a reproducible alternative for distribution network automation. Full article