Search Results (100)

Gram staining remains a primary diagnostic method in clinical microbiology, but manual interpretation of stained smears is time-consuming, subject to inter-operator variability, and impractical for continuous 24/7 monitoring. Automated detection offers faster turnaround, standardized classification independent of operator experience, and scalability for routine water-quality surveillance. This study evaluates seven YOLO-based architectures for four-class detection of Gram-stained bacterial cells (Gram-positive cocci, Gram-negative cocci, Gram-positive rods, Gram-negative rods) in microscopic images at 1000× magnification. Four baseline nano-scale models (YOLOv10n, YOLO11n, YOLO12n, YOLO26n) were trained and compared with three modified architectures based on YOLO26, including the proposed YOLO26-Refined, which extends the feature pyramid to the P2/4 level, applies a CBAM attention module after the P3 stage, disables shortcut connections in neck blocks, and uses reg_max = 16 for Distribution Focal Loss. All models were trained on a dataset of 5994 annotated images (69/21/10 split) using an NVIDIA RTX 4080 GPU. YOLO26-Refined achieved the best overall performance, with mAP50 = 0.934, mAP50-95 = 0.616, Precision = 0.846, and Recall = 0.888, outperforming the YOLO26n baseline (mAP50 = 0.923) by 0.011. Per-class results show the highest accuracy for Gram-negative rods (mAP50 = 0.965) and the lowest for Gram-positive rods (mAP50 = 0.890). With 2.63 million parameters, 9.9 GFLOPs, and an inference latency of approximately 1.8 ms per image on an RTX 4080 GPU (batch = 1, FP16), the model remains suitable for edge deployment, supporting its application in automated water-quality microbiological monitoring under the IRN BR28712227 research grant. Full article

Piezoelectric flexure micro-positioning stages are essential micromotion actuators for micro-assembly, atomic force microscopy and nano-manufacturing, but intrinsic hysteresis nonlinearity of piezoelectric stacks distorts the linear voltage-to-displacement mapping and induces significant micro-positioning errors. Conventional hysteresis compensation based on offline-calibrated Krasnosel’skii-Pokrovskii (KP) models cannot adapt to time-varying excitation, whereas state-of-the-art adaptive KP control requires auxiliary dynamic equations and imposes high computational overhead on miniature real-time controllers. To address these limitations, this paper develops a single-degree-of-freedom micromotion positioning device equipped with symmetric two-stage displacement amplification mechanisms and straight circular flexure hinges. ANSYS finite element simulations validate the mechanical stiffness, structural safety and linear amplification characteristic of the micro-positioning stage, achieving a maximum output stroke of 95.95 μm. A discretized KP hysteresis model is constructed to accurately capture the asymmetric rate-dependent hysteresis of piezoelectric stacks. On this basis, a lightweight adaptive inverse control framework is proposed, which realizes online tuning of KP weights through gradient descent iteration only relying on real-time position feedback, eliminating static pre-calibration and extra dynamic correction links. Tracking experiments under 0.1–2 Hz sinusoidal waveforms and 3–7 V variable-amplitude sinusoidal waveforms are implemented. Experimental results show that the proposed approach reduces the root-mean-square error (RMSE) by 7.41–85.65% and the mean absolute percentage error (MAPE) by 7.56–87.81% compared with uncompensated open-loop micromotion control. The combined micro-flexure mechanical design and adaptive hysteresis compensation strategy greatly improves positioning accuracy and anti-interference capacity, offering a low-computation technical route for high-performance micro-positioning systems. Full article

Tomato leaf disease detection in natural environments is challenged by subtle early-stage symptoms, complex backgrounds, leaf occlusion, and scale variation, which can lead to missed detections, false detections, and unstable leaf localization. Meanwhile, practical agricultural applications impose higher requirements on model lightweightness and edge-deployment capability. To address these issues, this study proposes DFR-YOLOv12n, a lightweight tomato leaf disease detection model based on YOLOv12n that integrates detail-preserving downsampling, feature enhancement, and regression optimization. First, a multi-source dataset collected in natural environments was constructed and curated, covering eight categories: bacterial spot, early blight, late blight, leaf mold, mosaic virus disease, septoria leaf spot, yellow leaf curl virus disease, and healthy leaves. Second, SPDConv was introduced into key downsampling layers to preserve fine-grained disease-related visual cues. The A2C2f_DEConv module was incorporated into the P3 feature fusion branch to enhance leaf texture and disease-related appearance features under complex backgrounds. In addition, MPDIoU was adopted to optimize bounding box regression and improve whole-leaf localization under occlusion and background interference. The optimal model configuration was determined through insertion-position, module comparison, and ablation experiments. Compared with the baseline model, DFR-YOLOv12n increased Precision, Recall, and mAP@0.5 from 86.8%, 76.9%, and 86.5% to 88.1%, 81.7%, and 88.6%, respectively. Meanwhile, FLOPs decreased from 5.83 G to 5.27 G, the parameter count decreased from 2.51 M to 2.25 M, and the model size decreased from 5.22 MB to 4.71 MB. Furthermore, the model was successfully deployed and validated on the Jetson Nano platform, demonstrating its potential for edge applications. The results indicate that DFR-YOLOv12n achieves a favorable balance among detection accuracy, model complexity, and deployment feasibility, providing a reference for intelligent tomato leaf disease detection in natural environments. Full article

To meet the increasing demands for large stroke and low cross-axis coupling in precision instruments such as atomic force microscopy (AFM), a low-coupling parallel piezoelectric nanopositioning stage based on a pseudo-symmetric guiding mechanism is proposed. By integrating a compact flexure-based lever amplification mechanism with a parallel pseudo-symmetric guiding structure, the design achieves effective suppression of cross-axis coupling while maintaining a relatively large motion range. A static model is established based on Castigliano’s second theorem, and electromechanical coupled finite element analysis is performed to evaluate the output characteristics and dynamic behavior. A prototype is fabricated and experimentally validated. The results demonstrate that the stage achieves a travel range of 121 μm × 122 μm, a cross-axis coupling error ratio of 1.1%, resolutions of 7 nm and 5 nm along the X- and Y-axes, respectively, and a first natural frequency of 476 Hz. The proposed design provides a feasible approach for achieving a balance among large stroke, low coupling, and high dynamic performance in piezoelectric nanopositioning systems. Full article

Precision tilt stages capable of high angular resolution and low cross-axis coupling are essential for applications such as free-space optical communication, adaptive optics, and micro/nano-positioning. In this study, a two-degree-of-freedom compliant tilt stage based on differential actuation of positive and negative Poisson’s ratio folded-beam structures is proposed. The stage incorporates four circumferential compliant motion units, each consisting of a W-shaped positive Poisson’s ratio folded beam, an M-shaped negative Poisson’s ratio folded beam, a lever amplification mechanism, and compliant decoupling leaf springs. By exploiting the opposite out-of-plane deformation tendencies of the two folded-beam types under identical input forces, a push–pull differential driving effect is generated, enabling independent tilting motion about two orthogonal axes with enhanced angular output. The lever amplification mechanisms enlarge the small displacement of the piezoelectric actuators, while the decoupling leaf springs suppress parasitic motion and reduce cross-axis coupling. A static analytical model is established based on compliance analysis and force–moment equilibrium. The model predictions are validated through finite element analysis, with errors of 4.77% and 4.80% for the two axes, respectively. Experimental results obtained from a stereolithography-fabricated prototype demonstrate maximum tilt angles of 9.19 mrad and 8.80 mrad about the x- and y-axes under a 150 V driving voltage, while the corresponding coupling angles are only 0.043 mrad and 0.040 mrad, yielding coupling ratios below 0.5%. The proposed design achieves a favorable combination of compact monolithic structure, effective displacement amplification, and excellent decoupling performance, offering a practical solution for precision optical adjustment, beam steering, and micro/nano-positioning systems. Full article

Background: Neoadjuvant partial breast irradiation using stereotactic body radiotherapy (SBRT) has emerged as a strategy to induce tumor and immune responses in early-stage, low-risk breast cancer. While prior studies have demonstrated encouraging response rates and evidence of immune modulation, the optimal radiotherapy regimen for immune priming remains unclear. SIGNAL 2.0 is a randomized phase II trial designed to compare the biological and immunological impact of a single-fraction versus three-fraction neoadjuvant SBRT. Materials and Methods: Sixty-one postmenopausal patients ≥ 50 years with unifocal, hormone positive, node-negative invasive ductal carcinoma < 3 cm were randomized 1:1 to receive either 21 Gy in one fraction or 30 Gy in three fractions, delivered to the tumor in the prone position. Core biopsies were collected pre-SBRT and 14–20 days post-SBRT at the time of surgery. Immune markers were assessed using tumor-infiltrating lymphocyte (TIL) scoring, NanoString nCounter PanCancer Immune Profiling, and NanoString GeoMx Digital Spatial Profiling (DSP). Results: Available tumor samples from 47 patients underwent paired tissue analysis. Three-fraction SBRT induced 200 differentially expressed genes, including enrichment of pathways related to adaptive immune activation, with significant increases in expression levels of macrophages, dendritic cells, neutrophils and CD8 T-cells. Proteomic profiling also identified a significant increase in the expression levels of neutrophils, Treg cells, macrophages, and NK cells in the tumor microenvironment of the samples from patients receiving the three-fraction regimen. Conclusions: Neoadjuvant SBRT induces measurable immune activation, with three-fraction regimens generating more extensive transcriptional, proteomic, and cellular immune changes than a single fraction. Three-fraction neoadjuvant SBRT may provide superior immune priming, providing a foundation for future trials integrating neoadjuvant radiotherapy with immunomodulatory therapies. Full article

Recycled aggregates (RAs) from construction and demolition waste (CDW) provide substantial circular-economy benefits, yet their elevated porosity, adhered mortar, and heterogeneity typically impair the mechanical performance and durability of recycled aggregate concrete (RAC). This PRISMA 2020-compliant systematic review synthesises 2180 records (2015–2026) to evaluate advanced strategies for enhancing RA quality prior to structural use. This paper critically compares removal-based treatments (mechanical, thermal, acid cleaning) with strengthening and densification approaches, including accelerated carbonation, pozzolanic and nano-silica coatings, polymer impregnation, microbial-induced calcium carbonate precipitation (MICP), and modified mixing methods such as triple-stage mixing (TSMA). Evidence shows that while all RA types (including recycled fine aggregate (RFA), recycled coarse aggregate (RCA), and their combination (RFCA)) can slightly reduce compressive strength and 30% replacement serves as a critical threshold, beyond this, strength loss accelerates, particularly in RCA and RFCA mixes. However, accelerated carbonation and TSMA consistently refine the interfacial transition zone, reduce water absorption by 17–30%, and recover 85–94% of natural aggregate concrete strength. Bio-deposition reduces water absorption by 13–21%, while acid/silica fume treatments improve late-age strength but carry environmental trade-offs. This review formulates a practice-oriented implementation framework for structural-grade RAC. Sustainability analyses indicate that carbonated RA can achieve net-positive CO₂ abatement when under low-carbon energy supply. A mechanistic schematic is presented to synthesise treatment-to-pore-structure/durability pathways across the four principal treatment routes, and a quantitative synthesis plot compares water absorption reductions across all treatment types using 13 data points drawn from included studies. A structured treatment comparison evaluates the energy intensity, industrial scalability, CO₂ footprint, and technology readiness level for each strategy. The remaining challenges include a lack of hybrid treatment studies, limited real-scale durability data, and insufficient mechanistic models linking treatment to pore structure evolution. This review recommends harmonised durability-based criteria and updates to standards (e.g., BS 8500, EN 12620) to support the scalable deployment of treated RA. Full article

A piezoelectric (PZT) nanopositioning stage with large stroke and low crosstalk is relatively appealing for microdisplacement operation. Rhombus and lever amplifiers are used to increase the overall displacement amplification ratio (DAR), and the symmetry of the amplification structure reduces the coupling error. At the same time, decoupling beams are used to balance the stiffness in the x- and y-directions, thereby reducing the crosstalk of the stage. Theoretical analysis, kinematics modeling, and finite element simulation were carried out to verify the feasibility of the PZT nanopositioning stage, and an experimental prototype was manufactured. The prototype test results indicate that the workspace of the stage is 312 μm × 312 μm, the DAR is approximately 9.3, and the first natural frequency is approximately 76 Hz. Moreover, the area efficiency is 6.03, which indicates that the stage is compact. The results prove that the developed stage possesses a good property for microdisplacement operation. Full article

This work introduces the MassSeg-Framework, a fully automatic two-stage pipeline for breast mass analysis in mammography that integrates YOLOv11-based detection with Chan–Vese ACM refinement to achieve accurate mass localization and segmentation with a lightweight computational footprint. The framework was trained and evaluated on two publicly available datasets using consistent experimental protocols. In the detection stage, YOLOv11-nano was the most effective architecture, with a confidence threshold of 0.4, achieving statistically significant mAP50 values of 0.862 and 0.709 on the dINbreast and dCBIS datasets, respectively. These results confirm that a moderate threshold preserves clinically relevant true-positive candidates, which is particularly important for screening-oriented settings where missed lesions are costly. In the segmentation stage, the proposed framework achieved mean DICE scores of 0.721 and 0.700 on the test sets of the same datasets, demonstrating consistent overlap with expert annotations. Compared with state-of-the-art approaches that commonly assume lesion-centered ROIs or rely on heavier backbones, the proposed pipeline addresses a more realistic scenario by performing automatic detection followed by segmentation while maintaining substantially lower computational requirements. This balance between performance and efficiency makes the MassSeg-Framework a promising tool for scalable mammography analysis, particularly in resource-constrained environments or high-throughput screening workflows that require rapid processing. Full article

The Jiaodong gold-mineralized area is one of the most significant gold districts in China. The newly discovered Moshan gold deposit is hosted in the Late Jurassic Queshan granite, previously considered a prospecting blind zone. In this study, pyrite from the Moshan gold deposit is examined as the primary research subject. To elucidate the ore-forming processes and genetic mechanisms of this deposit, we conducted a comprehensive mineralogical and geochemical study on pyrite, the principal gold-bearing mineral. EPMA and LA-MC-ICP-MS analyses reveal that the pyrite is slightly sulfur-deficient (average S/Fe ratio of 1.976) and exhibits trace element variations (As, Co, and Ni) strongly correlated with distinct metallogenic stages. Gold occurs in various forms, including visible inclusion gold, fracture gold, and invisible nano-particulate gold (Au⁰). The in situ sulfur isotope δ³⁴S values range from 7.11‰ to 9.40‰ (average 8.00‰), displaying high homogeneity and a positive deviation from the troilite in the Canyon Diablo iron meteorite. By integrating pyrite S-Fe relationships, Co-Ni-As systematics, and sulfur isotope characteristics, the study indicates that the Moshan gold deposit originates from a magmatic-hydrothermal source. The ore-forming materials predominantly derive from Mesozoic granite-derived magmatic-hydrothermal fluids, with a minor contribution from crustal basement materials. The depth of mineralization is interpreted as mid-shallow. These findings not only highlight the metallogenic potential of the Queshan granite and clarify the genetic relationship between the Moshan gold deposit and other regional gold deposits but also provide a novel theoretical foundation and technical support for deep gold exploration in the Jiaodong region. Full article

This study investigated the effect of superheated steam (SS) assisted glycosylation modification on the flavor profile of oyster peptides (OP), and explored the correlation between key flavor compounds and glycosylation degree using Gas Chromatography–Ion Mobility Spectrometry (GC-IMS) and nano-scale Liquid Chromatography coupled with High-Resolution Mass Spectrometry (nano-LC/HRMS). The results indicated that SS treatment accelerated the glycosylation process, reduced free amino groups level, and distinguished their unique flavor through E-nose. GC-IMS analysis detected 64 signal peaks including 13 aldehydes, 6 ketones, 7 esters, 6 alcohols, 2 acids, 2 furans and 5 other substances. And it was revealed that SS-mediated glycosylation treatment reduced the levels of fishy odorants like Heptanal and Nonanal, while promoting the pleasant-smelling alcohols and esters. In addition, Pearson correlation showed a positive correlation between excessive glycation and the increase in aldehydes, which might cause the recurrence of undesirable fishy notes. Further nano-LC/HRMS analysis revealed that arginine and lysine acted as the main sites for glycosylation modification. Notably, glycosylated peptides such as KAFGHENEALVRK, DSRAATSPGELGVTIEGPKE, generated by mild SS treatment could convert into ketones and pyrazines in subsequent reactions, thereby contributing to overall sensory enhancement. In conclusion, SS treatment at 110 °C for 1 min significantly improved the flavor quality of OP and sustains improvement in subsequent stages, providing theoretical support for flavor optimization of oyster peptides. Full article

Flexure-based nanopositioning stages have emerged as indispensable tools in advanced fields such as nanotechnology, semiconductor manufacturing, and biomedical engineering, where nanometer-scale precision is paramount. This paper presents a comprehensive review of the state-of-the-art in flexure-based nanopositioning, systematically examining the three critical and interconnected domains of geometric design, theoretical modeling, and advanced control strategies. This review begins by analyzing fundamental design principles, including motion decoupling, stiffness-range trade-offs, and various structural topologies (serial, parallel, and hybrid), highlighting how they achieve high precision and reject disturbances. It then delves into analytical and computational modeling techniques, from pseudo-rigid-body models and beam theory to finite element analysis, which are essential for predicting system behavior and guiding design optimization. A core section of this review is dedicated to control methodologies, providing a critical analysis of active resonant control for damping mechanical vibrations, classical and robust control for stability under uncertainties, and modern adaptive and learning-based techniques for handling nonlinearities and time-varying dynamics. Furthermore, this review addresses persistent challenges such as bandwidth limitations, performance trade-offs, and the integration of complex multi-axis systems. Finally, it outlines future research directions, emphasizing the promising potential of data-driven modeling, artificial intelligence-enhanced control, and a holistic mechatronic co-design approach to push the boundaries of precision, speed, and robustness in next-generation nanopositioning systems. This work aims to serve as a systematic reference and synthesis for researchers by integrating a vast body of literature and providing a clear perspective on the development of high-performance nanopositioning stages. Full article

The aim of the study was to determine the effect of Swiss chard powder (SCP) as a natural nitrite source on the volatile compounds and other qualitative properties of heat-treated sucuk (HTS). Three formulations were created for the production of HTS: control (no nitrite addition), synthetic nitrite (SN, 150 mg/kg NaNO₂ addition), and natural nitrite from Swiss chard powder (SCPN) (SCP equivalent to 150 mg/kg NaNO₂). The HTS production was carried out under controlled conditions. Physicochemical and microbiological properties of the HTS were investigated during the production stages. The final product was analyzed for volatile compounds, residual nitrite, and sensory properties. A higher mean pH value was found in the SCPN group in comparison with other groups (p < 0.05). In all production stages, the lowest a_w values were observed in the presence of SCPN (p < 0.05). The highest mean L* value was determined in the group with SN (p < 0.05). Groups containing SN or SCPN exhibited higher a* values compared to the control during fermentation, heat treatment, and drying. The SN group had the lowest TBARS value during all these stages (p < 0.05). There was no significant difference in the amount of residual nitrite between the SCPN and SN groups (p > 0.05). In terms of sensory parameters, nitrite groups (SCPN and SN) had higher values than the control group (p < 0.05). Lactic acid bacteria exhibited good growth during fermentation in all groups. Although SCP positively affected many volatile compounds, this effect was not strong enough to alter the sensory properties of the product. Correlation analysis of volatile compounds revealed that the control group was significantly different from the groups using SN or SCPN. Additionally, similar characteristics in volatile compounds and sensory attributes were observed in the SN and SCPN groups. As a result, characteristics of the final products were not usually adversely affected by the use of SCP in HTS production. Full article

The Eastern Kazakhstan Gold Belt is a major black-shale-hosted gold province in Central Asia where the main types of deposits comprise mineralized zones with auriferous sulfides (micro- and nano-inclusions of gold and refractory gold) and quartz veins with visible gold. The quartz vein deposits are economically less important but may potentially represent the upper parts of bigger ore systems concealed at depth. In this work, the mineralogy of the quartz vein deposits and related wall rock alteration zones was studied using microscopy and SEM-EDS analysis, and the geochemical dispersion of the ore elements in primary alteration haloes was documented utilizing spatial distribution maps and statistical treatment methods. The studied auriferous quartz veins are classified as epizonal black-shale-hosted orogenic gold deposits. The veins generally have linear shapes with an average width of ca. 1 m and length up to 150 m and contain high-grade native gold with minor amounts of sulfides. In supergene oxidation zones, the native gold is closely associated with Fe-hydroxide minerals cementing brecciated zones within the veins. The auriferous quartz veins are usually enclosed by the wall rock alteration envelopes, where two types of alteration are distinguished. Proximal phyllic alteration (sericite-albite-pyrite ± chlorite, Fe-Mg-Ca carbonates, arsenopyrite, and pyrrhotite) develops as localized alteration envelopes, and pervasive carbonation accompanied by chlorite ± sericite and albite is the dominant process in the distal alteration zones. The rocks within the alteration zones are enriched in Au and chalcophile elements, and three groups of chemical elements showing significant positive mutual correlation have been identified: (1) an early geochemical assemblage includes V, P, and Co (±Ni), which are the chemical elements characteristic for black shale formations, (2) association of Au, As, and other chalcophile elements is distinctly overprinting, and manifests the main stage of sulfide-hosted Au mineralization, and (3) association of Bi and Hg (±Sb and U) includes the chemical elements that are mobile at low temperatures, and can be explained by activity of the late-stage hydrothermal or supergene fluids. The chalcophile elements show negative slopes from proximal to distal alteration zones and form overlapping positive anomalies on spatial distribution mono-elemental maps. Thus, the geochemical methods can provide useful tools to delineate the ore elemental associations and to outline reproducible anomalies for subsequent regional gold prospecting. Full article

To achieve efficient and accurate detection of blueberry fruit ripeness, this study proposes a lightweight yet high-performance object detection model—CES-YOLO. Designed for real-world blueberry harvesting scenarios, the model addresses key challenges such as significant visual differences across ripeness stages, complex occlusions, and small object sizes. CES-YOLO introduces three core components: the C3K2-Ghost module for efficient feature extraction and model compression, the SEAM attention mechanism to enhance the focus on critical fruit regions, and the EMA Head for improved detection of small and densely packed targets. Experiments on a blueberry ripeness dataset demonstrated that CES-YOLO achieved 91.22% mAP50, 69.18% mAP95, 89.21% precision, and 85.23% recall, while maintaining a lightweight structure with only 2.1 M parameters and 5.0 GFLOPs, significantly outperforming mainstream lightweight detection models. Extensive ablation and comparative studies confirmed the effectiveness of each component in improving detection accuracy and reducing false positives and missed detections. This research offers an efficient and practical solution for automated recognition of fruit and vegetable maturity, supporting broader applications in smart agriculture, and provides theoretical and engineering insights for the future design of agricultural vision models. To further demonstrate its practical deployment capability, CES-YOLO was successfully deployed on the NVIDIA Jetson Orin Nano platform, where it maintained real-time detection performance, with low power consumption and high inference efficiency, validating its suitability for embedded edge computing scenarios in intelligent agriculture. Full article