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Microfluidic electro-viscoelastic manipulation of extracellular vesicles
No full textMicrofluidic technology has created new opportunities for developing innovative tools for biological applications. Given the significance of extracellular vesicles (EVs), extensive research has focused on developing microfluidic techniques for EV isolation. This research protocol presents electro-viscoelastic microfluidics as a novel approach for manipulating EVs. The system leverages the viscoelasticity of the suspending medium along with an externally applied electric field to alter EV motion within a microchannel. These findings suggest that our electro-viscoelastic microfluidic system has the potential for further development to be used for EV isolation.</p
Enhanced YOLOv8 Model for Accurate and Real-Time Remote Sensing Target Detection
Get PDFCurrent remote sensing image object detection algorithms often struggle with false positives, missed targets, and suboptimal accuracy. To address these issues, we propose an improved YOLOv8 network (PIYN) solution achieved through targeted modifications to the YOLOv8 architecture. The backbone of YOLOv8 utilizes a Cross-Stage Partial (CSP) structure that includes two convolutions, called a faster C2f module. Firstly, we infuse the C2f module integrating an Efficient Multi-Scale Attention (EMA) mechanism, which enhances the module's ability to process information across various scales. Secondly, we introduce a Compact Path Aggregation Network (Compact-PAN) structure within the neck of the network, which reduces the computational complexity of the model. Finally, replacing the Complete Intersection over Union (CIoU) loss function with the Weighted Intersection over Union (WIoU) loss refines the model's detection accuracy. Additionally, we applied K-fold cross-validation on the dataset to mitigate overfitting. Experiments using the extensive Dataset for Object Detection in Aerial images (DOTA) and the Dataset for Object Recognition in Optical Remote Sensing Imagery (DIOR) reveal PIYN's effectiveness: there is a 2.43% and 2.56% increase in Mean Average Precision (mAP) over YOLOv8, respectively, alongside a 4.49% reduction in GFLOPs. These results demonstrate PIYN's capability to enhance accuracy while maintaining efficiency and solidify its progressive and practical impact, particularly for smart city applications
Strategic Marketing Tensions in Sustainable Business Models: A Conceptual Approach Through Customer Value Propositions and Stewardship
Get PDFSustainable business models (SBMs) inherently involve tensions, which are contradictory or misaligned demands that companies must consider simultaneously. However, there is a gap in the literature regarding the relevance and linkage of these tensions to strategic marketing considerations, including positioning, competitiveness, differentiation, and a company's interaction with customers. This study aims to identify a set of tensions that arise in the strategic marketing of SBMs and to explore how these tensions can be responded to by companies. The study adopts a conceptual methodology, applying customer value propositions (CVPs) as a structured strategic marketing lens to explore tensions. Further, stewardship is suggested as an ontological approach that shapes the strategic marketing responses to tensions for the collective good of future generations. The resulting framework outlines how companies can embrace SBM tensions, including their hierarchical intensity, make sense of complexity and address the dominance of unsustainable models through strategic marketing mechanisms.</p
Fast pyrolysis pathway for production of sustainable aviation fuel (SAF) from demolition wood: Experimental and process simulation approach
No full textThe escalating adverse climate impacts of aviation industry have attracted the attention of research towards the production of sustainable aviation fuels (SAF) for mitigating the climate change. This study aims to investigate the demolition wood as a potential feedstock to produce SAF through fast pyrolysis process. A steady-state process simulation model was developed in Aspen Plus® and validated experimentally. The simulation model developed for SAF production comprises pyrolysis process, hydrotreating of bio-oil, fractionation of hydrotreated-oil, production of H 2 gas through Proton exchange membrane (PEM) electrolyzer, purification of aqueous stream, and combustion of char blocks. The process simulation model has produced 52.8 wt% bio-oil, 20.5 wt% char, and 10.8 wt% gases by using yield-based pyrolysis reactor at operating temperature of 500 °C. Experimental results have demonstrated 49.9 wt% bio-oil yield at 500 °C pyrolysis temperature and 1 s reactants residence time. The simulation model indicated 12.2 wt% SAF yield, and physiochemical properties of SAF were also found consistent with the ASTM D7566 standard. It was also indicated that around 0.07 kg of H 2 per kg of bio-oil is needed for hydro-processing reactions at 99.9 % purity of H 2 gas. The process simulation model also estimated that 36.3 MW of electrical power, 6.9 MW of external heating utility and 11.7 MW of external cooling utility were required to produce 0.12 kg of SAF per kg of feedstock. Overall, the research provides a platform to examine the development of SAF production process through the fast pyrolysis of demolition wood, followed by hydro-processing and fractionation.</p
Preparing a social impact bond in a Nordic welfare state: governance challenges and hybrid responses
No full textPurposeThis study aims to examine the preparation of a complex Social Impact Bond (SIB) project in Finland, exploring how challenges and solutions reflect the interplay between new public management (NPM) and new public governance (NPG) logics. It contributes to debates on the institutional adaptability of SIBs beyond Anglo-American contexts.Design/methodology/approachThe authors conduct a longitudinal case study of the Children’s SIB II in Finland, analysing data from 21 stakeholder interviews. Five preparation phases are identified and examined for governance dynamics and challenge-response logics.FindingsThe findings show how SIB preparation involved hybrid governance, combining NPM tools, such as performance-based incentives, with NPG principles like trust-building and cross-sector collaboration. While many challenges were initially framed through NPM logics, their resolution often leaned towards NPG-style responses, highlighting the adaptive use of relational governance practices. A key insight is the critical role of a publicly funded intermediary in framing the SIB, mobilizing networks and embedding the instrument within national welfare discourses.Social implicationsHybrid governance tools like SIBs can reinforce trust-based public-private cooperation and support developing responses to complex social issues, but they also require significant institutional capacity.Originality/valueThis study extends the literature on SIBs by examining their preparation in a Nordic welfare state context, distinct from the Anglo-American settings where SIBs have been most studied. It contributes novel insights into how hybrid governance unfolds in such contexts, particularly how NPG-style solutions emerge even when problems are framed through NPM logics. It also highlights the overlooked role of public institutional intermediaries in shaping SIB development beyond technical and financial coordination.<br/
A brittle failure evaluation of a semi-elliptical surface crack in a pipe mock-up using three variations of the advanced master curve assessment accounting for ductile crack growth, constraint loss and crack front length
No full textRecently, an experiment on a ferritic pipe mock-up, with a semi-elliptical surface crack, loaded in four-point bending, failed by brittle fracture following ductile crack growth. The experiment serves as a case-study to validate advanced methods for assessing brittle failure affected by constraint-loss, ductile crack growth and the crack front length. Previous work has focused on the determination of the component J-R curve. In this work, three variations of the advanced Master Curve assessment are conceptualized and applied to evaluate the probability of brittle failure of the pipe. The sensitivity of the brittle failure prediction to the three variations of the advanced method is investigated by gradually increasing the complexity of the assessment and by varying the input parameters related to constraint, ductility and the crack front length. The J-integral and constraint along the crack front are evaluated using finite element modelling. The results demonstrate the significance of the component J-R curve in the assessment and provide insight into how the input parameters and the assessment method affect the brittle failure prediction. The work contributes to the efficient operation of pressurized components and affects standards development
A Novel L<sub>1</sub>-and-L<sub>2</sub>-Norm-Integrated Parameter Identification Model for Robot Calibration
No full textRobots promote the social development by enhancing production efficiency, reducing labor costs, and improving service quality. Meanwhile, their application fields such as healthcare, transportation, and education can drive technological advancement and innovation, thus fostering economic growth and improving our quality of life. However, due to mechanical wear from prolonged operation, the robot absolute positioning error can reach several millimeters, thus it is impossible for them to perform precise tasks. To address this intractable problem, this study innovatively proposes a robot calibration method (FPSA) combining the search algorithm based on proportion integration differentiation (PID) controller and fuzzy strategy for adjusting hyperparameter, its novelties include: 1) designing a novel L1-and-L2-norm-integrated parameter identification model, then search algorithm [PID search algorithm (PSA)] based on PID controller is adopted to solve this model, which achieves the accurate identification of robot kinematic errors; and 2) developing an efficient fuzzy strategy for adjusting hyperparameter to achieve hyperparameter adaptation in the robot parameter identification model, thereby effectively enhancing the calibration computation efficiency and accuracy. Moreover, we conduct extensive calibration experiments on an HSR JR680 robot. These experimental results demonstrate that compared with other advanced calibration algorithms, the maximum error of the proposed FPSA calibration method is 9.57% higher than that of the most accurate identification model solved by PSA algorithm, which has single L2 norm regularization and objective function. Therefore, this research provides excellent calibration service for a robot, thus contributing to the prosperous development of application fields such as industrial manufacturing and smart agriculture.</p
