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Thermal, hardness, and tribological assessment of PEEK/CoCr composites
Shadowless amyloid imaging with quantitative birefringence contrast
Telecentric stereo 3D imaging with isotropic micrometer resolution bridges macro- and microscale in small Lepidopterans
Abstract We present a straightforward, application-driven telecentric stereo 3D-measurement system for high-precision measurements, designed for applications ranging from industrial quality control to biological research including scanning of Lepidoptera moths. Utilizing a dual-camera setup with telecentric lenses and structured illumination, our system achieves lateral resolution of 8.0 $$\upmu$$ m and axial resolution of 4.46 $$\upmu$$ m in a measurement volume of 11 mm $$\times 11$$ mm $$\times 6$$ mm. We address challenges typically encountered when using standard libraries like OpenCV, e.g. in extrinsic parameter estimation using a dedicated calibration method that corrects for a potential model mismatch due to telecentricity. Our approach adapts existing methods, such as telecentric stereo vision and structured illumination, into an optimized, user-friendly system tailored for life science research, enabling detailed 3D-reconstructions of scattering objects, such as small moths, with isotropic micrometer accuracy. This work presents an application-driven approach for biological 3D-metrology by integrating existing technologies (telecentric stereo vision, structured illumination) into a specialized imaging platform suitable for non-invasive morphological studies. Unlike conventional CT or microscopic approaches, our method provides a balance of precision, scalability, and practical usability for non-expert users with the aim to study developmental changes in species under varying environmental conditions, while also methodically bridging the gap between macroscopic and microscopic resolution in biological imaging.
Adaptive context biasing in transformer-based ASR systems
Statistical variability in comparing accuracy of neuroimaging based classification models via cross validation
Ultrasensitive detection of amlodipine using plasmonic optical fiber sensors enhanced with graphene oxide and chitosan nanocomposite
Modulating the Binding Kinetics of Bruton’s Tyrosine Kinase Inhibitors through Transition-State Effects
Prospective changes in lipocalin-2 and adipocytokines among adults with obesity
Intermolecular Interactions in Direct Air Capture Materials: Insights from Charge Density Analysis
An effectiveness of deep learning with fox optimizer-based feature selection model for securing cyberattack detection in IoT environments
Predicting soil organic carbon with ensemble learning techniques by using satellite images for precision farming
Adaptive laboratory evolution of Blakeslea trispora under acetoacetanilide stress leads to enhanced β-carotene biosynthesis
Process optimization and modeling research for the defluoridation of water using a novel adsorbent of cellulose and hydroxyapatite nanocomposite
Machine learning-driven framework for realtime air quality assessment and predictive environmental health risk mapping
Abstract This research introduces a practical and innovative approach for real-time air quality assessment and health risk prediction, focusing on urban, industrial, suburban, rural, and traffic-heavy environments. The framework integrates data from multiple sources, including fixed and mobile air quality sensors, meteorological inputs, satellite data, and localised demographic information. Using a combination of machine learning techniques such as Random Forest, Gradient Boosting, XGBoost, and Long Short-Term Memory (LSTM) networks the system predicts pollutant concentrations and classifies air quality levels with high temporal accuracy. Interpretability is achieved through SHAP analysis, which provides insight into the most influential environmental and demographic variables behind each prediction. A cloud-based architecture enables continuous data flow and live updates through a web dashboard and mobile alert system. Visual risk maps and health advisories are generated every five minutes to support timely decision-making. The framework not only forecasts pollution trends but also identifies vulnerable populations through spatial overlays. Future validation will include real-world sensor deployment and comparison with health impact records to ensure both scientific accuracy and community relevance.
Distal Scaffold Flexibility Modulates Eyring Activation Parameters in Re(I) Substitution Reactions: A Case for Dynamics as the “Thematic Third Coordination Sphere”
Crystalline Peptoid Nanofibers with a Single-Unit Cell Cross Section
Anatomic insights into the vascularized supraclavicular lymph node flap and a novel design for enhanced lymphedema surgery
Switchable linear to circular polarization conversion in reflection and transmission modes based on vanadium-dioxide
Abstract A design of a switchable dual-mode linear-to-circular polarization converter (LTC-PC) in the terahertz (THz) band is reported based on vanadium dioxide (VO2). Adjusting the VO2 state allows the converter to alternate between the transmission and reflection modes. In the insulating state, VO2 enables transmission mode operation for a forward x- or y-polarized wave. LTC polarization conversion occurs within the frequency bands of 1.26–1.47 THz and 1.83–1.85 THz. Moreover, this mode yields an LTC polarization conversion at a frequency of 1.7 THz. The polarizer operates in reflection mode when VO2 is in the metallic state. Two conversion bands are identified for circular polarization within the frequency bands of 0.93–1.67 THz and 1.80–1.86 THz. The dual-mode polarization converter achieves axial ratios below 3 dB and a polarization conversion efficiency greater than 0.8. Surface current distributions reveal the polarization conversion mechanisms. Furthermore, we analyze the polarization ellipses of both reflected and transmitted waves at various frequencies across the operational bands. We anticipate that the proposed design, featuring high performance and dual functionality, will be applicable in THz communication systems and sensors.