Search Results (717)

Agarwood, valued for its resin, has long been used in perfumery, incense, and traditional medicine. Its resin is primarily derived from species of Aquilaria and is produced through a still-unknown process in response to biotic or abiotic stress. Concerns regarding agarwood’s sustainability and conservation have emerged because of the substantial loss of natural resources due to overharvesting and illegal trade. To address these concerns, artificial techniques are being used to produce agarwood. The mechanism underlying agarwood production must be elucidated to enhance yield. The authentication of agarwood species is challenging because of morphological similarities between pure and hybrid Aquilaria species. Techniques such as DNA barcoding, molecular marker assessment, and metabolomics can ensure accurate identification, facilitating conservation. Artificial intelligence and machine learning can support this process by enabling rapid, automated identification on the basis of genetic and phytochemical data. Advances in resin induction methods (e.g., fungal inoculation) and chemical induction treatments are improving yield and quality. Endophytic fungi and bacteria promote resin production at minimal harm to the tree. Agarwood’s pharmacological potential—antimicrobial, anti-inflammatory, and anticancer effects—has driven research into bioactive compounds such as sesquiterpenes and flavonoids for the development of novel drugs. This systematic review synthesized current evidence on species authentication, induction techniques, and pharmacological properties. The findings may guide future research aimed at ensuring sustainable use and enhancing the medicinal value of agarwood. Full article

As a common signal sensing device in pulsed eddy current detection, coil sensors often have parameter offset problems in practical applications. The error in the receiving coil parameters will have a great impact on the early signal. In order to ensure the accuracy of the early signal, this paper first analyzes the response characteristics of the receiving coil and the influence of the coil parameters on the accuracy of signal deconvolution and establishes the mathematical relationship between the response signal and the characteristic parameters, and between the characteristic parameters and the receiving coil parameters under active underdamped oscillation. Subsequently, the parameter feature extraction errors under different state switching capacitors were compared through simulation analysis, the state switching capacitor value was determined, and the receiving coil parameter solution method based on the Levenberg–Marquardt (LM) algorithm was determined based on the parameter feature extraction results. The experimental results demonstrate that the proposed method achieves a capacitance estimation error of just 0.0159% and an inductance error of 0.158%, effectively minimizing early signal distortion and enabling precise identification of receiving coil parameters. Full article

Subject to magnetic saturation, temperature rise, and other factors, the electrical parameters of permanent magnet synchronous motors (PMSMs) in marine electric propulsion systems exhibit time-varying characteristics. Existing parameter identification algorithms fail to fully satisfy the requirements of high-performance PMSM control systems in terms of accuracy, response speed, and robustness. To address these limitations, this paper introduces multi-innovation theory and proposes a novel multi-innovation extended Kalman filter (MIEKF) for the identification of key electrical parameters of PMSMs, including stator resistance, d-axis inductance, q-axis inductance, and permanent magnet flux linkage. Firstly, the extended Kalman filter (EKF) algorithm is applied to linearize the nonlinear system, enhancing the EKF’s applicability for parameter identification in highly nonlinear PMSM systems. Subsequently, multi-innovation theory is incorporated into the EKF framework to construct the MIEKF algorithm, which utilizes historical state data through iterative updates to improve the identification accuracy and dynamic response speed. An MIEKF-based PMSM parameter identification model is then established to achieve online multi-parameter identification. Finally, a StarSim RCP MT1050-based experimental platform for online PMSM parameter identification is implemented to validate the effectiveness and superiority of the proposed MIEKF algorithm under three operational conditions: no-load, speed variation, and load variation. Experimental results demonstrate that (1) across three distinct operating conditions, compared to forget factor recursive least squares (FFRLS) and the EKF, the MIEKF exhibits smaller fluctuation amplitudes, shorter fluctuation durations, mean values closest to calibrated references, and minimal deviation rates and root mean square errors in identification results; (2) under the load increase condition, the EKF shows significantly increased deviation rates while the MIEKF maintains high identification accuracy and demonstrates enhanced anti-interference ability. This research has achieved a comprehensive improvement in parameter identification accuracy, dynamic response speed, convergence effect, and anti-interference performance, providing an electrical parameter identification method characterized by high accuracy, rapid dynamic response, and strong robustness for high-performance control of PMSMs in marine electric propulsion systems. Full article

Robust speed estimation in induction motors (IM) is essential for control systems (especially in sensorless drive applications) and condition monitoring. Traditional model-based techniques for inverter-fed IM provide a high accuracy but rely heavily on precise motor parameter identification, requiring multiple sensors to monitor the necessary variables. In contrast, model-independent methods that use rotor slot harmonics (RSH) in the stator current spectrum offer a better adaptability to various motor types and conditions. However, many of these techniques are dependent on full-band processing, which reduces noise immunity and increases computational cost. This paper introduces a novel subband signal processing approach for rotor speed estimation focused on RSH tracking under both steady and non-steady states. By limiting spectral analysis to relevant content, the method significantly reduces computational demand. The technique employs an advanced time-frequency analysis for high-resolution frequency identification, even in noisy settings. Simulations and experiments show that the proposed approach outperforms conventional RSH-based estimators, offering a robust and cost-effective solution for integrated speed monitoring in practical applications. Full article

Mucormycosis is a rare invasive fungal disease in pediatric patients with hematological malignancies and is associated with poor outcomes. We present a fulminant and ultimately fatal case of rhino-orbito-cerebral mucormycosis, addressing important issues including clinical signs and symptoms, diagnostic approaches and the challenges of timely diagnosis. The patient was an 11-year old girl undergoing re-induction chemotherapy for Central Nervous System relapse of B-cell precursor acute lymphoblastic leukemia. She presented six days into the second course of chemotherapy in profound neutropenia with aggravating headaches, painful abducens nerve palsy and anisocoria. At first (day −3), no significant radiological or ophthalmological correlations were found, and methyl–prednisolone was started due to suspected vasculitis following ICU admission. After further clinical deterioration, a second MRI scan (day 0) revealed a prolonged occlusion of the left carotid artery, which was successfully stented in a neuroradiological intervention (day +1). However, during the next day the child developed clinical signs indicating severe cerebral dysfunction. An emergency CT scan showed complete infarction of the left hemisphere including a progredient perfusion deficit and beginning brain edema. Based on the unfavorable prognosis, best supportive care was initiated, and the patient deceased on day +2. Pathological and microbiological workup identified thrombotic infarction in all major cerebral arteries. While microscopy was suspicious for mucormycosis, nested PCR from retained blood specimens confirmed the genus Lichtheimia. Final NGS on brain tissue led to the identification of Lichtheimia ramosa. This case illustrates the rapidity and severity of Mucorales infection. It shows the importance of early clinical suspicion and the need for an aggressive laboratory testing algorithms. The stratification of risk factors and definition of red flags may be a future task fighting these infections. Full article

Somatic embryogenesis (SE) is a key plant regeneration technique involving the reprogramming of somatic cells into embryogenic structures. This developmental transition is regulated by complex genetic and epigenetic mechanisms, including post-translational modifications such as SUMOylation—the covalent attachment of small ubiquitin-like modifier (SUMO) proteins to target proteins, influencing their function, stability, and interactions. While SUMOylation is known to regulate plant development and stress responses, its role in SE has remained unknown. In this study, we investigated the involvement of the SUMOylation pathway in SE induction in Medicago truncatula. Using BLASTp analysis with known SUMO pathway proteins from Arabidopsis thaliana and Glycine max, we identified 10 homologous genes in M. truncatula. Phylogenetic relationships, gene structure, and conserved motif analyses confirmed their evolutionary conservation and characteristic domains. Expression profiling revealed significant upregulation of SUMO pathway genes—including Mt SUMO2, Mt SAE1-2, Mt SCE1a-b, Mt MMS21, and Mt PIAL2—in embryogenic cell lines during early SE induction. Additionally, in silico prediction of SUMOylation sites and SUMO-interacting motifs (SIMs) in 12 key SE regulatory proteins indicated a broad potential for SUMO-mediated regulation. These findings suggest that SUMOylation may contribute to the acquisition of embryogenic competence during somatic cell reprogramming in plants. Full article

Magnesium (Mg) alloys, particularly Mg AZ31, have emerged as promising biomaterials for orthopedic applications due to their biodegradability and favorable mechanical characteristics. Among these, the Mg AZ31+SPF alloy, subjected to hydrothermal (HT) treatment, has demonstrated enhanced bioactivity. Our previous research established that this surface modification supports the osteogenic differentiation of human mesenchymal stem cells (hMSCs) by modulating both canonical and non-canonical signaling pathways, including those implicated in osteogenesis, hypoxic response, exosome biogenesis, and lipid metabolism. In the present study, we extended our investigation to assess the effects of Mg AZ31+SPF+HT and Mg AZ31+SPF extracts on murine pre-osteoclasts (RAW 264.7 cells) over 3- and 6-day treatment periods. The primary objectives were to evaluate biocompatibility and to investigate potential impacts on osteoclastogenesis induction and miRNA expression profiles. Methods: To assess cytocompatibility, metabolic activity, DNA integrity, and morphological alterations in RAW 264.7 cells were evaluated. Osteoclast differentiation was quantified using TRAP staining, alongside the assessment of osteoclastogenic marker expression by qRT-PCR and ELISA. The immunomodulatory properties of the extracts were examined using multiplex BioPlex assays to quantify soluble factors involved in bone healing. Additionally, global miRNA expression profiling was performed using a specialized panel targeting 82 microRNAs implicated in bone remodeling and inflammatory signaling. Results: Mg AZ31+SPF+HT extract exhibited high biocompatibility, with no observable adverse effects on cell viability. Notably, a significant reduction in the number of TRAP-positive and multinucleated cells was observed relative to the Mg AZ31+SPF group. This effect was corroborated by the downregulation of osteoclast-specific gene expression and decreased MMP9 protein levels. Cytokine profiling indicated that Mg AZ31+SPF+HT extract promoted an earlier release of key cytokines involved in maintaining the balance between bone formation and resorption, suggesting a beneficial role in bone healing. Furthermore, miRNA profiling revealed a distinct regulatory signature in Mg AZ31+SPF+HT-treated cells, with differentially expressed miRNAs associated with inflammation, osteoclast differentiation, apoptosis, bone resorption, hypoxic response, and metabolic processes compared to Mg AZ31+SPF-treated cells. Conclusions: Collectively, these findings indicate that hydrothermal treatment of Mg AZ31+SPF (resulting in Mg AZ31+SPF+HT) attenuates pre-osteoclast activation by influencing cellular morphology, gene and protein expression, as well as post-transcriptional regulation via modulation of miRNAs. The preliminary identification of miRNAs and the activation of their regulatory networks in pre-osteoclasts exposed to hydrothermally treated Mg alloy are described herein. In the context of orthopedic surgery—where balanced bone remodeling is imperative—our results emphasize the dual significance of promoting bone formation while modulating bone resorption to achieve optimal implant integration and ensure long-term bone health. Full article

Background/Objectives: The progression of antibiotic resistance is increasingly recognized as a dynamic and time-dependent phenomenon, challenging conventional diagnostics that define resistance as a binary trait. Methods: Biomolecules have fingerprints in Fourier-transform infrared spectroscopy (FTIR). The targeting of specific molecular groups, combined with principal component analysis (PCA) and machine learning algorithms (ML), enables the identification of bacteria resistant to antibiotics. Results: In this work, we investigate how effective classification depends on the use of different numbers of principal components, spectral regions, and defined resistance thresholds. Additionally, we explore how the time-dependent behavior of certain spectral regions (different biomolecules) may demonstrate behaviors that, independently, do not capture a complete picture of resistance development. FTIR spectra were obtained from Staphylococcus aureus exposed to azithromycin, trimethoprim/sulfamethoxazole, and oxacillin at sequential time points during resistance induction. Combining spectral windows substantially improved model performance, with accuracy reaching up to 96%, depending on the antibiotic and number of components. Early resistance patterns were detected as soon as 24 h post-exposure, and the inclusion of all three biochemical windows outperformed single-window models. Each spectral region contributed distinctively, reflecting biochemical remodeling associated with specific resistance mechanisms. Conclusions: These results indicate that antibiotic resistance should be viewed as a temporally adaptive trajectory rather than a static state. FTIR-based biochemical profiling, when integrated with ML, enables projection of phenotypic transitions and supports real-time therapeutic decision-making. This strategy represents a shift toward adaptive antimicrobial management, with the potential to personalize interventions based on dynamic resistance monitoring through spectral biomarkers. Full article

Mollusc shells serve as valuable biogeochemical archives of natural or anthropogenic processes occurring in the aquatic environment throughout the life of the molluscs. One such process is trace element pollution, which can be assessed by analyzing the elemental composition of mollusc shells. However, different mollusc species accumulate elements in their shells from the aquatic environment at varying concentrations, and specific patterns of this accumulation remain largely unknown. In the present study, we measured the concentrations of 33 elements in the shells of five commercially important Black Sea molluscs, all collected from the same site, using inductively coupled plasma mass spectrometry. The species were ranked according to the number of elements with the highest concentrations in their shells as follows: Crassostrea gigas (9) = Rapana venosa (9) = Anadara kagoshimensis (9) > Flexopecten glaber ponticus (4) > Mytilus galloprovincialis (2). Cluster analysis of Pearson’s coefficients of correlation of elemental concentrations in the molluscan shells revealed significant separation of C. gigas, F. glaber ponticus, and M. galloprovincialis. Multivariate ordination analyses allowed the accurate classification of >92.3% of shell samples using as few as four elements (Fe, As, Sr, and I). Linear discriminant analysis revealed the probability of separation of all species based on the concentrations of these elements in their shells being not lower than 79%. The applied multivariate approach based on the analysis of four base elements in shells can help not only in the taxonomic identification of molluscs, but also, upon appropriate calibration, in monitoring medium-term dynamics of trace elements in the aquatic environment. Full article

Currently, wind turbines utilize doubly fed induction machines that incorporate a frequency converter in the rotor circuit to manage slip energy. This setup ensures a stable voltage amplitude and frequency that align with the alternating current. It is crucial to accurately determine the parameters of the equivalent circuit from the rotor side of the vector control system of the frequency converter. The objective of this study is to develop a method for the preliminary identification of the doubly fed induction machines parameters by analyzing the rotor current decay curves using Newton’s method. The numerical estimates of the equivalent circuit parameters a doubly fed induction machines with a fixed short-circuited rotor are obtained during the validation of the results on a real plant. It is along with the integral errors of deviation between the experimental rotor current decay curve and the response of the adaptive regression model. The integral errors do not exceed 4% in nearly all sections of the curves. It is considered acceptable in engineering practice. The developed algorithm for the preliminary identification for the parameters of the doubly fed induction machines substitution scheme can be applied with the configuring machines control systems, including a vector control system. Full article

The Junggar Basin contains a large amount of coal resources and is an important coal production base in China. The coal seam in Zhundong coalfield has a large single-layer thickness and high content of inertinite, but large particle Fe-sulphide minerals are associated with coal seams in some mining areas. A series of economic and environmental problems caused by the combustion of large-grained Fe-sulphide minerals in coal have seriously affected the economic, clean and efficient utilization of coal. In this paper, the ultra-thick coal seam of the Xishanyao formation in the Yihua open-pit mine of the Zhundong coalfield is taken as the research object. Through the analysis of coal quality, X-ray fluorescence spectrometer test of major elements in coal, inductively coupled plasma mass spectrometry test of trace elements, SEM-Raman identification of Fe-sulphide minerals in coal and LA-MC-ICP-MS test of sulfur isotope of marcasite, the coal quality characteristics, main and trace element characteristics, macro and micro occurrence characteristics of Fe-sulphide minerals and sulfur isotope characteristics of marcasite in the ultra-thick coal seam of the Xishanyao formation are tested. On this basis, the occurrence state and genesis of large particle Fe-sulphide minerals in the ultra-thick coal seam of the Xishanyao formation are clarified. The main results and understandings are as follows: (1) the occurrence state of Fe-sulphide minerals in extremely thick coal seams is clarified. The Fe-sulphide minerals in the extremely thick coal seam are mainly marcasite, and concentrated in the YH-2, YH-3, YH-8, YH-9, YH-14, YH-15 and YH-16 horizons. Macroscopically, Fe-sulphide minerals mainly occur in three forms: thin film Fe-sulphide minerals, nodular Fe-sulphide minerals, and disseminated Fe-sulphide minerals. Microscopically, they mainly occur in four forms: flake, block, spearhead, and crack filling. (2) The difference in sulfur isotope of marcasite was discussed, and the formation period of marcasite was preliminarily divided. The overall variation range of the δ³⁴S value of marcasite is wide, and the extreme values are quite different. The polyflake marcasite was formed in the early stage of diagenesis and the δ³⁴S value was negative, while the fissure filling marcasite was formed in the late stage of diagenesis and the δ³⁴S value was positive. (3) The coal quality characteristics of the thick coal seam were analyzed. The organic components in the thick coal seam are mainly inertinite, and the inorganic components are mainly clay minerals and marcasite. (4) The difference between the element content in the thick coal seam of the Zhundong coalfield and the average element content of Chinese coal was compared. The major element oxides in the thick coal seam are mainly CaO and MgO, followed by SiO₂, Al₂O₃, Fe₂O₃ and Na₂O. Li, Ga, Ba, U and Th are enriched in trace elements. (5) The coal-accumulating environment characteristics of the extremely thick coal seam are revealed. The whole thick coal seam is formed in an acidic oxidation environment, and the horizon with Fe-sulphide minerals is in an acidic reduction environment. The acidic reduction environment is conducive to the formation of marcasite and is not conducive to the formation of pyrite. (6) There are many matrix vitrinite, inertinite content, clay content, and terrigenous debris in the extremely thick coal seam. The good supply of peat swamp, suitable reduction environment and pH value, as well as groundwater leaching and infiltration, together cause the occurrence of large-grained Fe-sulphide minerals in the extremely thick coal seam of the Xishanyao formation in the Zhundong coalfield. Full article

This paper presents a structured and experimentally validated approach to the parameter identification, modeling, and real-time speed control of a brushless DC (BLDC) motor. Electrical parameters, including resistance and inductance, were measured through DC and AC testing under controlled conditions, respectively, while mechanical and electromagnetic parameters such as the back electromotive force (EMF) constant and rotor inertia were determined experimentally using an AVL dynamometer. The back EMF was obtained by operating the motor as a generator under varying speeds, and inertia was identified using a deceleration method based on the relationship between angular acceleration and torque. The identified parameters were used to construct a transfer function model of the motor, which was implemented in MATLAB/Simulink R2024b and validated against real-time experimental data using sinusoidal and exponential input signals. The comparison between simulated and measured speed responses showed strong agreement, confirming the accuracy of the model. A proportional–integral (PI) controller was developed and implemented for speed regulation, using a low-cost National Instruments (NI) USB-6009 data acquisition (DAQ) and a Kelly controller. A first-order low-pass filter was integrated into the control loop to suppress high-frequency disturbances and improve transient performance. Experimental tests using a stepwise reference speed profile demonstrated accurate tracking, minimal overshoot, and robust operation. Although the modeling and control techniques applied are well known, the novelty of this work lies in its integration of experimental parameter identification, real-time validation, and practical hardware implementation within a unified and replicable framework. This approach provides a solid foundation for further studies involving more advanced or adaptive control strategies for BLDC motors. Full article

Peanut (Arachis hypogaea L.) is a globally important oilseed cash crop, yet its limited genetic diversity and unique reproductive biology present persistent challenges for conventional crossbreeding. Traditional breeding approaches are often time-consuming and inadequate, mitigating the pace of cultivar development. Essential for double fertilization and programmed cell death (PCD), DUF679 membrane proteins (DMPs) represent a membrane protein family unique to plants. In the present study, a comprehensive analysis of the DMP gene family in peanuts was conducted, which included the identification of 21 family members. Based on phylogenetic analysis, these genes were segregated into five distinct clades (I–V), with AhDMP8A, AhDMP8B, AhDMP9A, and AhDMP9B in clade IV exhibiting high homology with known haploid induction genes. These four candidates also displayed significantly elevated expression in floral tissues compared to other organs, supporting their candidacy for haploid induction in peanuts. Subcellular localization prediction, confirmed through co-localization assays, demonstrated that AhDMPs primarily localize to the plasma membrane, consistent with their proposed roles in the reproductive signaling process. Furthermore, chromosomal mapping and synteny analyses revealed that the expansion of the AhDMP gene family is largely driven by whole-genome duplication (WGD) and segmental duplication events, reflecting the evolutionary dynamics of the tetraploid peanut genome. Collectively, these findings establish a foundational understanding of the AhDMP gene family and highlight promising targets for future applications in haploid induction-based breeding strategies in peanuts. Full article

In acute lymphoblastic leukemia (ALL), neutropenia and fever of unknown origin may occur, indicating the use of antimicrobials to control a probable infection. However, in 60–70% of cases there is no obvious infectious focus so treatment is empirical, increasing the risk of developing systemic inflammatory response syndrome (SIRS). The construction of a prognostic model of fever and development of SIRS based on the identification of endogenous molecules, called alarmins or damage-associated molecular patterns (DAMPs) and inflammatory cytokines, can help identify children with ALL and fever or SIRS and who do not have an infection. A cohort of 30 children with recently diagnosed ALL and absence of infectious microorganisms before starting the remission induction phase was studied. Two groups were identified: (1) a group with SIRS (fever, tachycardia, tachypnea, and leukopenia, without focus of infection) and (2) a group without SIRS. The DAMPs, namely HMGB1 and S100A8 proteins, were quantified by ELISA and inflammatory mediators were determined by multiple protein analysis. The medians of DAMPs and inflammatory mediators in children with SIRS were higher than in children who did not have SIRS, and the delta values of the biomarkers studied in patients with and without SIRS showed important differences, with statistically higher medians in patients with SIRS compared to those without SIRS. HMGB1 together with IL-1β, IL-8, IL-10, and MCP-1 can serve as biomarkers to identify children with ALL and fever or SIRS who should not receive antimicrobial treatment because the origin of their fever is not due to an infectious agent. Full article

Aim: To explore the experiences, beliefs, and values of patients who participated in a two-arm randomized clinical trial assessing a nurse-led intervention program for chronic pain self-management, which demonstrated positive effects on pain reduction, depression, and anxiety, and on health-related quality of life 24 months after completion of the program. Design: Descriptive phenomenological qualitative study. Methods: Patients were recruited via telephone, informed about the study, and invited to participate in an individual interview at a place of their choice (hospital or home). All interviews were audiotaped, and an inductive thematic analysis was performed. Results: Seven interviews were carried out between both groups. Six emerging categories were found: effective relationship with the healthcare system, learning to live with pain, family and social support, behaviors regarding pain, resources for self-management, and concomitant determinants. Conclusions: Patients report key aspects that help us to understand the impact of this type of nurse-led group intervention: the intrinsic therapeutic effect of participating in the program itself, the ability to learn to live with pain, the importance of family and social support, the modification of pain-related behaviors, and the identification of resources for self-care. The findings highlight the need for gender-sensitive, individualized care approaches to chronic pain, addressing stigma and social context. Expanding community-based programs and supporting caregivers is essential, as is further research into gender roles, family dynamics, and work-related factors. Full article