Search Results (518)

Vibration monitoring plays a crucial role in assessing the condition and operational safety of electric drive systems. In many industrial applications, scalar control is widely used due to its simplicity and reliability, yet its influence on vibration transmission within interconnected machines remains insufficiently explored. This study addresses the problem of understanding how mechanical vibrations are transmitted between a scalar-controlled induction motor coupled with an AC generator. A comparative experimental investigation was conducted using two different configurations of drive units, incorporating either an induction or a synchronous generator. Vibrations were measured at various operating speeds and analysed using different sensor types to ensure repeatability and reliability of the results. The findings have revealed distinct patterns of vibration transmission between the motor and generator, highlighting the importance of drive system configuration and measurement methodology. A novel approach to data presentation is proposed by normalising vibration levels between machines, offering a clearer interpretation of vibration amplification or damping effects. The results contribute to the development of diagnostic techniques and the optimisation of scalar-controlled drive designs. Full article

In tokamak-based nuclear fusion systems, powering the coils to control the plasma is a challenge that involves design choices that are a mix between advanced and traditional approaches. Each tokamak coil requires peculiar driving conditions and needs specific design activities. This paper deals with power supply design assessment for the Divertor (DIV) Coils in the Divertor Tokamak Test (DTT) facility. The design constraints of high-current (5500 A) and relatively low-voltages lead to the comparison of an SCR-based AC–AC converter (cycloconverter) with an IGBT-based DC–AC inverter with devices in a parallel solution and with interleaved modulation. The design assessment of two converter solutions to drive the DIV coils with the control issues were explored and described. Several simulation results were carried out to define the DIV coils operative conditions. Furthermore, an electro-thermal analysis on the used IGBT or thyristor devices was carried out considering the losses and the highest temperatures obtained in the conditions of maximum stress for the components. Full article

The spatial distribution of plant species is a crucial indicator of the mechanisms driving competition or coexistence both within and between populations and communities. Analyzing these patterns provides essential insights into fundamental ecological processes and aids in evaluating ecological hypotheses. To study the spatial distribution of dominant tree species and their associations both within and among species, we established a 25-hectare forest plot in Lushan Mountain. We employed the g(r) function alongside three null models—complete spatial randomness (CSR), heterogeneous Poisson (HP), and antecedent condition (AC)—to analyze spatial patterns and assess species interactions at various life stages. Additionally, we examined the relationships between spatial distributions and environmental factors such as soil properties and topography using Berman’s test. Our results showed that all 12 dominant tree species exhibited significant aggregation under the CSR model; however, the scales of aggregation were reduced under the HP model. We also found evidence of aggregation among multiple species across different life stages and tree layers under CSR. Notably, this pattern persisted under the AC model but was limited to specific spatial scales. Furthermore, elevation, topographical convexity, and the total content of soil nitrogen (N) and carbon (C) were identified as statistically significant predictors of species distributions. Overall, these findings highlight that both biological and environmental factors play a vital role in shaping plant spatial patterns across different scales. Full article

Green innovation (GI) is a key measure for enterprises to realize green transformation and sustainable development. Top management teams’ environmental attention (TMTEA) plays a critical role in shaping organizational strategic direction, value orientation, management mode, and behavioral patterns, serving as a micro-foundation for GI. Based on exploring the relationship between TMTEA and GI, this study adopts the ambidexterity theory to categorize dual green innovation (Dual_GI) into breakthrough green innovation (BGI) and progressive green innovation (PGI), and examines the impact of TMTEA on Dual_GI from the perspectives of external government environmental regulation (GER) and internal absorptive capacity (AC). Drawing on the attention-based view (ABV), this study uses data samples of Chinese A-share listed companies from 2010 to 2022 and establishes a fixed-effect model to empirically test this relationship. The results show the following: (1) TMTEA has a positive impact on corporate Dual_GI, and the promotion effect on PGI is more significant. (2) Both GER and AC can positively moderate the impact of TMTEA on Dual_GI, and both have a stronger moderating effect on TMTEA on PGI. (3) Further analysis shows that this driving effect is more obvious in state-owned enterprises, non-heavy polluting enterprises and enterprise maturity, and TMTEA can also drive Dual_GI to improve sustainable development performance. This study deepens the research scope and boundary conditions of TMT’s micro-psychological cognition and GI. It provides new insights for managers in emerging economies to rebalance their companies’ economic benefits and environmental transformation. Full article

Investigating the compositional characteristics of rhizosphere soil bacterial communities of Chinese seabuckthorn across different distribution areas and their relationship with habitat factors holds significant value for the development and utilization of characteristic medicinal plant resources in the Qinghai–Tibet Plateau. This study targeted rhizosphere soil from 12 distribution areas of Chinese seabuckthorn on the Qinghai–Tibet Plateau. By integrating measurements of soil and climatic parameters with high-throughput sequencing and redundancy analysis (RDA), the research systematically elucidated the characteristics of rhizosphere bacterial communities and their environmental driving mechanisms. The results revealed that rhizosphere bacterial communities of Chinese seabuckthorn across all 12 distribution areas were dominated by Proteobacteria, Acidobacteriota, and Actinobacteriota. Among them, the R2 habitat exhibited the highest amplicon sequence variant counts (3496), while R1, R8, R9, and R12 habitats showed significantly lower counts. α/β diversity analysis revealed that Shannon, Ace, and Chao1 indices in R2 and R7 habitats were significantly higher than those in R1 and R8. Regarding community aggregation patterns, soil bacterial communities in R1, R9, and R12 habitats exhibited the highest aggregation, while those in R2 and R11 habitats showed relatively lower aggregation. Functional prediction demonstrated that Metabolism dominated across all distribution areas (50.40–52.02%), with the R11 habitat exhibiting exceptionally high metabolic function abundance (>9300). Clustering analysis partitioned the 12 habitats into two distinct groups: one comprising R2, R6, R7, R9, R10, and R11, and the other containing the remaining six habitats. Redundancy analysis (RDA) further clarified that habitat factors, including altitude, soil water content (SWC), east longitude (EAST), and pH, were key drivers shaping bacterial community structure. This study underscores the pivotal regulatory role of environmental factors in shaping rhizosphere microbial diversity, community structure, and functional profiles of Chinese seabuckthorn, thereby providing a valuable scientific foundation for the sustainable development of characteristic medicinal plant resources on the Qinghai–Tibet Plateau. Full article

Heparan sulfate proteoglycans serve as initial attachment sites for several viruses and bacteria. Recent studies suggest that SARS-CoV-2 similarly exploits these glycosaminoglycans, facilitating conformational changes in the spike protein that promote the interaction between the receptor-binding domain (S1-RBD) and the cellular angiotensin-converting enzyme 2 receptor (ACE2), thereby triggering the virus internalization process. The molecular details that drive this process, particularly the co-receptor role of heparan sulfate (HS), remain incompletely understood. The interaction between an HS hexasaccharide (hexa) and the N343 glycosylated S1-RBD of the wild-type (WT) and Omicron variant of SARS-CoV-2 was investigated. The conformational properties of hexa with these S1-RBDs in unbound and bound states are explored using multiple independent MD simulations; the protein binding epitope of hexa, as well as the details of its interaction with S1-RBD of the Omicron variant, are characterized by comparing experimental and theoretical ¹H STD NMR signals. This investigation identifies the role played by the glycosyl moiety at N343 in potentially affecting this interaction in both WT and Omicron S1-RBD, explaining the observed low specificity and multi-modal nature of the interaction between HS oligosaccharides and these S1-RBDs. Full article

The Complement C3a Receptor (C3aR) plays a multifaceted role along the varying temporal phases of brain injury following cerebral ischemia. C3aR is a G-protein-coupled receptor (GPCR) that binds to its ligand, C3a an anaphylatoxin generated during activation of the complement cascade. During ischemia, complement is activated as part of the initial inflammatory response, with C3aRs playing a time-dependent role in both brain injury and repair mechanisms. In the acute phase (minutes to hours post-ischemia), C3aR activation promotes the recruitment of immune cells and the release of chemokines and cytokines, driving blood–brain barrier (BBB) permeability and brain edema. During the subacute phase (hours to days post-ischemia), C3aR continues to modulate immune cell activity, worsening secondary brain injury, although emerging evidence suggests that C3aR activation in this phase may also aid in the clearance of cellular debris and cell survival. In the chronic phase (days to weeks post-ischemia), chronically elevated C3aR activity can prolong neuroinflammation and impair recovery, whereas controlled C3aR signaling in the subacute/chronic phase can activate reparative pathways (e.g., microglial phagocytosis, astrocyte trophic support). As a result, targeting the C3aR requires careful timing to optimize its benefits. Given the dual impact of C3aR activation, which serves to exacerbate injury in the acute phase but supports repair beginning in the subacute and chronic phases, a targeted therapeutic approach should focus on context- and time-dependent modulation of the C3a/C3aR axis. This strategy would involve blocking the C3aR during the acute phase to reduce inflammation and BBB breakdown while controlling C3a signaling in later phases to promote tissue repair. Full article

Poplar (Populus L. species), a fast-growing temperate species, forms plantations with high productivity and biomass, with its litter sustaining key functions in nutrient cycling, microbial diversity, and carbon storage. Litter microbial communities drive decomposition, particularly in early stages, this initial phase is characterized by the leaching of water-soluble carbon and nutrients from the litter, which creates a readily available resource pulse that facilitates rapid microbial colonization and activation. This process is followed by the activation of microbial enzymes and the immobilization of nutrients, collectively initiating the breakdown of more recalcitrant litter materials. Under rising global nitrogen deposition, we conducted a field randomized block experiment in 13-year-old pure poplar (Populus deltoides L. ‘35’) stands, with three nitrogen addition treatments: N0 (0 g N·m⁻²·yr⁻¹), N2 (10 g N·m⁻²·yr⁻¹), and N4 (30 g N·m⁻²·yr⁻¹). In the initial phase of litter decomposition, we measured the soil properties and litter traits, the litter microbial community composition, and its taxonomic and phylogenetic diversity indices. The results indicate that nitrogen addition altered microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), soil NO₃⁻-N, and accelerated litter decomposition rates. The microbial community in leaf litter responded to nitrogen addition with increased phylogenetic clustering (higher OTU richness and NRI), which suggests that environmental filtering exerted a homogenizing selective pressure linked to both soil and litter properties, whereas the microbial community in branch litter responded to nitrogen addition with increased taxonomic diversity (higher OTU richness, Shannon, ACE, and Chao1), a pattern associated with litter properties that likely alleviated nitrogen limitation and created opportunities for more taxa to coexist. The observed differences in response stem from distinct substrate properties of the litter. This study elucidates microbial taxonomic and phylogenetic diversity responses to nitrogen addition during litter decomposition, offering a scientific foundation for precise microbial community regulation and sustainable litter management. Full article

Osteosarcoma (OS), the most common primary malignant bone tumor, arises in highly mechanosensitive tissue and exhibits marked heterogeneity and resistance to conventional therapies. While molecular drivers have been extensively characterized, the role of mechanical stimuli in OS progression remains underexplored. Here, we identify the transient receptor potential vanilloid 1 (TRPV1) channel as a key regulator of mechanotransduction and drug responsiveness in OS cells. Using uniaxial cyclic stretch, we show that aggressive U-2 OS cells undergo TRPV1-dependent perpendicular reorientation, unlike the inert SAOS-2 cells. Confocal microscopy, immunohistochemistry, and atomic force microscopy reveal that nanomolar concentrations of capsaicin—a well-characterized TRPV1 agonist—chemically mimic this mechanical phenotype, altering metastatic traits including adhesion, edge architecture, migration, nuclear-to-cytoplasmic ratio, and sensitivity to doxorubicin and cisplatin. TRPV1 activation, whether mechanical or chemical, induces subtype-specific effects absent in healthy hFOB osteoblasts. Notably, it differentially regulates nuclear localization of the proto-oncogene Src in U-2 OS versus SAOS-2 cells. Corresponding changes in Src and acetylated histone H3 (acH3) levels support a role for TRPV1 in modulating the Src–acH3 mechanosignaling axis. These effects are tumor-specific, positioning TRPV1 as a mechanosensitive signaling hub that integrates mechanical and chemical cues to drive epigenetic remodeling and phenotypic plasticity in OS, with potential as a therapeutic target in aggressive, drug-resistant subtypes Full article

Increasing the litter size in sheep is a primary objective in breeding programs, driving sustained interest in identifying candidate functional genes and molecular markers associated with fecundity. The known FecD mutation in the LEPR gene has been shown to regulate reproductive traits by influencing the ovulation rate of Davisdale sheep. However, the relationship between single-nucleotide polymorphisms (SNPs) in the LEPR and litter size remains unknown in Gobi short tail sheep and Sonid sheep. In this research, we found one novel variant and thirteen known variants through direct sequencing in Sonid sheep and Gobi short tail sheep and performed an association study in a large-scale population. The association analysis identified two SNPs (c.240C>T (rs159694506) and c.279C>T (rs159694508)) with significant litter size associations in Gobi short tail sheep (p < 0.01 ). In Sonid sheep, the c.240C>T (rs159694506), c.279C>T (rs159694508), g.41249772C>T (rs412130067), g.41249873A>C (rs425490800), g.41250357T>C (rs424307284), and g.41250358T>C (rs404651806) SNPs were significantly associated with litter size (p < 0.05 ). In addition, in GB sheep, the frequency of the litter-size-associated C allele at the c.240C>T (rs159694506) and c.279C>T (rs159694508) variants were significantly lower than that in Sonid sheep (SN), Mongolia sheep (MG), Ujimqin sheep (UM), Tan sheep (Tan), Hu sheep (Hu), and Small-tailed Han sheep (STH) populations. In SN sheep, the frequency of the litter-size-associated C allele at the c.240C>T (rs159694506) and c.279C>T (rs159694508) variant was significantly lower than that in the DPU. These findings provided valuable molecular markers pertinent to the fecundity of sheep, offering scientific evidence for the genetic improvement of these breeds. Full article

Threat activation or deactivation in the brain–body is associated with learned nocebo or placebo somatic effects induced by fake invasive medical–surgical procedures. Some functional somatic disorders (FSDs) originate as acute nocebo somatic effects and can become 30–50% of chronic somatic presentations to primary care physicians. Patients with FSD overutilize medical–surgical services, despite the lack of identified pathophysiology, and are at risk for morbidity from unintentional iatrogenic injury. The Conditioned Response Model (CRM) of learning postulates three innate mechanisms, modulated by trait hypnotizability, which drive placebo and nocebo somatic effects and FSD. The High Risk Model of Threat Perception (HRMTP) postulates 10 psychosocial risk factors that modulate threat perception, driving placebo and nocebo somatic effectsandbiologically embedded FSD. Psychosocial factors and the trait of high and low hypnotizability modulate threat and are postulated to reduce heart rate variability(HRV), inducing autonomic nervous system(ANS)dysregulation. Reduced HRV was found in a large (N = 6,891) sample of patients with FSD. A total of 50% of patients with FSD with chronic pain (n = 224) without identified pathophysiology had a Paradoxical Increase in hand Temperature (PTI) during experimental threat induction. The HRMTP predicts that PTI associated with ANS dysregulation is associated with the risk factor Adverse Childhood Experiences (ACEs). This ACE prediction was independently confirmed. Learning predicts that threat activation by unconscious neutral stimuli (CS) can amplify nocebo and FSD and can negate placebo effects in clinician–patient relationships. Identifying psychosocial risk factors that modulate threat perception enables the diagnosis of FSD by inclusion and not simply by excluding pathophysiology. Full article

The emergence of the SARS-CoV-2 JN.1 lineage in late 2023 marked a major shift in viral evolution. By January 2024, it had displaced XBB variants to become the dominant strain worldwide. JN.1 and its descendants are antigenically distinct from earlier Omicron subvariants, with approximately 30 additional spike mutations compared to XBB-derived viruses. The combination of these features alongside growing evidence of considerable immune evasion prompted the FDA to recommend that vaccine formulations be updated to target JN.1 rather than XBB.1.5. The continued dominance of JN.1-derived variants necessitates the characterization of viral infection in established animal models to inform vaccine efficacy and elucidate host–pathogen interactions driving disease outcomes. In this study, transgenic mice expressing human ACE2 were infected with SARS-CoV-2 subvariants JN.1, KP.2, and EG.5.1 to compare the pathogenicity of JN.1-lineage and XBB-lineage SARS-CoV-2 viruses. Infection with JN.1 and KP.2 resulted in attenuated disease, with animals exhibiting minimal clinical symptoms and no significant weight loss. In contrast, EG.5.1-infected mice exhibited rapid progression to severe clinical disease, substantial weight loss, and 100% mortality within 7 days of infection. All variants replicated effectively within the upper and lower respiratory tracts and caused significant lung pathology. Notably, EG.5.1 resulted in neuroinvasive infection with a significantly high viral burden in the brain. Additionally, EG.5.1 infection resulted in a significant increase in CD8⁺ T cell and CD11b⁺ CD11c⁺ dendritic cell populations in infected lungs. Full article

Model predictive control offers high-performance regulation for multiphase drives but is critically dependent on the accuracy of mathematical models for prediction, making it vulnerable to parameter mismatches and uncertainties. To achieve parameter-independent control across both healthy and faulty operations, this paper proposes a novel dynamic mode decomposition with control (DMDc)-based model predictive current control (MPCC) scheme for five-phase permanent magnet synchronous motors. The core innovation lies in constructing discrete-time state-space models directly from operational data via the open-loop DMDc identification, completely eliminating reliance on explicit motor parameters. Furthermore, an improved fault-tolerant strategy is developed to mitigate the torque ripple induced by inter-turn short-circuit (ITSC) faults. This strategy estimates the key fault characteristic, the product of the short-circuit ratio and current, through a spectral decomposition of the AC component in the q-axis current variations, bypassing the need for complex parameter-dependent observers. The derived compensation currents are seamlessly integrated into the predictive control loop. Experimental results comprehensively validate the effectiveness of the proposed framework, demonstrating a performance comparable to a conventional MPCC under healthy conditions and a significant reduction in torque ripple under ITSC fault conditions, all achieved without any prior knowledge of motor parameters or the retuning of controller gains. Full article

In view of the DC bus voltage fluctuation caused by the short-term periodic power demand of pulsed power loads (PPLs), this paper introduces a power allocation and tracking method for a hybrid energy storage system (HESS) with pulsed loads, aiming to improve the stability of the bus voltage. Firstly, a pulse power allocation and tracking method based on AC and DC components is proposed. Then, by introducing a current estimating method, a reference output current extraction from the AC component is obtained for model predictive control, which is used to control the supercapacitor converter, while the DC power is provided to inform the droop control to drive the battery converter. Finally, a frequency domain model is established to study the suppression effect of the control method on DC bus fluctuations, providing a reliable control scheme for HESS with pulsed power loads. Full article

Abrupt speed variations and motor start-ups have been pointed out as critical challenges in the framework of fault diagnostics in induction motor drives, namely inter-turn short circuit faults. Generally, abrupt accelerations influence the typical symptoms of the fault, and consequently, the fault detection becomes ambiguous, impacting prompt and effective decision-making. To overcome this issue, this study proposes an inter-turn short-circuit fault diagnostic technique for asymmetrical six-phase induction motor drives operating under both smooth and abrupt motor accelerations. A time–frequency domain spectrogram of the AC component extracted from the q-axis reference current signal serves as a reliable fault indicator. This technique stands out for the compromise between robustness and computational effort using only one control variable accessible in the model predictive control algorithm, thus discarding both voltage and current signals. Experimental tests involving various load torques and fault severities, in transient regimes, were performed to validate the proposed methodology’s effectiveness thoroughly. Full article