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Economic policy uncertainty and stock returns in China: the role of regulatory short-selling constraints
No full textWe examine the association between economic policy uncertainty (EPU) and expected stock returns and how short-selling regulations in China moderate this relationship. Consistent with the overpricing effects literature, we find a negative EPU–return relationship before the introduction of margin trade and short-selling (MTSS) program in 2010. However, after implementation of MTSS, the relationship turned positive for stocks without short-selling constraints, reflecting investors’ demand for higher risk compensation. Using propensity score matching and difference-in-differences, we demonstrate that relaxation of short-selling constraints mitigates overpricing and generates positive uncertainty premium. Our findings highlight the importance of short selling in pricing of uncertainty and implications for policymakers and investors.Journal of Emerging Market Financ
NLOS signal detection from early–late prompt correlators using convolutional LSTM network
No full textThe emerging development of Global Navigation Satellite System (GNSS) software receivers has opened new opportunities in diverse operations. However, non-line-of-sight (NLOS) concatenated signal reception is one prevalent deterioration factor causing positioning errors in urban scenarios. To enhance integrity and reliability through receiver autonomous integrity monitoring (RAIM) techniques in urban environments, distinguishing between line-of-sight (LOS) and NLOS signals facilitates the exclusion of NLOS channels: this is challenging due to uncertain signal reflections/refractions from diverse obstruction conditions in the built environment. Moreover, NLOS features show similarity to multipath effects like scattering and diffraction which causes difficulty in identifying the NLOS type. Recent work exploited NLOS detections with multi-correlator outputs using neural networks that outperform using signal strength techniques for NLOS detection. This paper proposes a neural network approach designed to recognise and learn spatial features among early, late, and prompt correlator outputs, differentiating between correlations, and also by memorising temporal features to acquire propagation information. Specifically, the spatial features of correlator IQ streams are derived from convolutional layers incorporated with concatenations, to formulate associate models like early-minus-late discrimination. A Recurrent Neural Network (RNN), i.e., long short-term memory (LSTM), is integrated to obtain comprehensive temporal features; hereby, a softmax classifier is appended in the last layer to distinguish between NLOS and LOS signals. By simulating synthetic datasets generated by a Spirent simulator and captured by a software-defined radio (SDR), the correlator outputs are acquired during the scalar tracking stage. The product of the proposed network demonstrates high performance in terms of accuracy, time consumption and sensitivity, affirming the efficiency of utilising early-stage correlations for NLOS detection. Moreover, an impact analysis of varying the sliding window length on NLOS discrimination underscores the need to fine-tune the parameter, as well as balancing accuracy, operation complexity and sensitivity.This work was performed under the ESA-funded project VTL4AV (NAVISP-EL1-066 bis)European Navigation ConferenceEngineering Proceeding
An exception algorithm to ease convergence in multistage turbomachinery throughflow calculations
No full textIterative solvers used in turbomachinery, spanning throughflow formulations and higher-order computational fluid dynamics (CFD), depend critically on how they are initialized. The starting state determines not only the number of iterations but often whether a solution is found at all when residuals are noisy or non-smooth. In such regimes, fast gradient updates can stall, oscillate, or violate bounds even when the underlying model is sound. This work introduces a solver-level exception algorithm that detects those failure signatures at run time and temporarily replaces the gradient step with a bounded, derivative-free fallback to reestablish a safe descent under strict feasibility limits. Control is returned to the fast path once a reliable reduction is found, preserving turnaround time in easy regions while adding robustness where the reference update is untrustworthy. The practical motivation is to reduce user workload and eliminate manual operating-point marching while enabling wider off-design coverage and characteristics traverses without a discernible accuracy or speed penalty. Although illustrated within a streamline curvature throughflow solver, the approach is general and can be interfaced with other throughflow methodologies and, more broadly, with higher-order CFD. Validation on single- and multistage axial-flow turbines shows improved robustness without a discernible accuracy or speed penalty within a state-of-the-art throughflow environment.Journal of Turbomachiner
Experimental investigation of flow characteristics of high-concentration ice slurry in pipes considering melting effects
No full textHigh-concentration ice slurry with phase change can be used as a pipe cleaning material, producing pollution-free effluents. The required characteristics of such slurry should be determined carefully before any cleaning process to slow down its melting rate and reduce cleaning costs. Excessive pump power should be avoided to minimize energy consumption, as well as high pressure on the pipeline wall to prevent pipe breakage. In this study, the flow and melting of high-concentration ice slurry were experimentally investigated in a closed-loop pipe system to examine the impact of key parameters on ice pigging. Results show that ice slurry exhibits effective cleaning performance during steady flow. The melting at the front of the slurry appears more pronounced due to the significant temperature difference between its front and the pipe wall, as well as the large heat exchange at the interface between the slurry front and the surrounding water. The melting rate of the ice slurry increases with flow acceleration, and the flowing distance increases with the slurry injection length, concentration, and flow velocity. The wall shear stress exerted by the ice slurry also increases with these parameters, and its rate of change is closely related to the velocity gradient near the boundary layer. A novel predictive formulation was developed to estimate the ice slurry flowing distance, featuring high accuracy and low experimental data requirements, by combining a physical modelling approach with a Gradient Boosting Regressor process. This research provides important information for the practical application of ice slurry in cleaning operations.Thermal Science and Engineering Progres
Space-based sensor fusion for refined space debris cataloguing
No full textMonitoring centimetre-class orbital debris is critical for spacecraft safety and the long-term sustainability of Low Earth Orbit (LEO), as fragments below current ground-based tracking thresholds can still cause mission-ending damage. This study presents the payload-level design of a dual-sensor architecture for space-based space situational awareness (SBSSA), comprising an active radar for Initial Orbit Determination (IOD) and a visible-band optical sensor for Precise Orbit Determination (POD).
For each payload, a metrics-driven trade space is developed that maps design variables to catalogue-relevant figures of merit. The optical analysis prioritises time-on-detector (dwell), angular accuracy, field of view (FOV), and illumination geometry; the radar analysis focuses on volumetric coverage, range and range-rate precision, dwell, and off-nadir viewing. Operational constraints from power, pointing, and communications are incorporated. Observation concepts are defined accordingly: the optical payload is considered in sun-synchronous orbit with anti-sun pointing to ensure favourable illumination and background conditions, while the radar payload employs off-nadir scanning to enlarge coverage within the 600–800 km debris band. Minimum detectability conditions are set to reflect catalogue integration requirements.
Representative Pareto-optimal designs are identified for both payloads and assessed against higher-level indicators, including catalogue maintenance potential, observation scheduling feasibility, and downlink load. The outcome yields concrete recommendations on optical aperture, detector format, FOV, and integration times, together with radar effective range, FOV geometry, and measurement precision. The translation from payload parameters to constellation-level implications—revisit frequency, handover latency, and the minimum number of spacecraft needed to sustain POD cadence—is quantified.
A simplified joint simulation of the two payloads is included only to check consistency between subsystem design and system-level behaviour. While individual payload requirements are met, temporal handover between radar detections and optical follow-ups emerges as a limiting factor, motivating refinement of orbital geometry, sensor co-location, and scheduling strategies prior to constellation optimisation.23rd IAA Symposium on Space Debris, Held at the 76th International Astronautical Congress (IAC 2025
Wireless data transfer system architecture for predictive maintenance of aircraft landing gear
Get PDFIn this paper, we describe the data transfer techniques used so far for landing gear andother critical aircraft systems predictive maintenance applications, as well as the available wireless data transfer techniques. Moreover, the architecture of a wireless transfer system forsending aircraft’s landing gear sensory data to a ground station is described, proposing the main guidelines in terms of middleware development and data security and fidelity.This research was funded by Innovate UK grant number 10040817, under the ATI/IUKAIAA SCITECH 2025 Foru
Enhancing safety performance in UK metal manufacturing: a revised framework to reduce fatal accidents
Get PDFFatal accidents in UK’s manufacturing sector are expected to remain the same or increase in coming years. This paper has tried to combat this issue by adapting and further developing a previously defined Safety Framework for the Paint Sector, to evaluate the safety performance of a metal manufacturing facility. To achieve this, the original Safety Framework was updated to align with the current British safety legislation outlined by the British Standards Institution. The framework was based on a three-level multi-attribute value theory (MAVT). Upon reviewing BSI 45001, the Safety Framework was founded upon the concept of Deming’s Plan, Do, Check, Act (PDCA) which is the foundation for the original framework, therefore, the first-level attributes remained consistent. The 13 attributes of the second level and 36 attributes of the third level were derived from the literature review and updated to relevant legislation. To develop the Safety Framework, the Delphi method was used. This included interviews that were conducted with employees and managers from either a Safety or Engineering background. The second part of the paper involved the improvement of the Safety Framework, based on the interview feedback. The main findings of the study revealed that the final Safety Framework has been deemed relevant for the Metal Manufacturing Sector by Industry Suitably Qualified and Experienced Personnel (SQEP). The majority of Interviewees deemed the Safety Framework to have a clear layout and easy to understand. The interviews and final Safety Framework suggested the importance of a company’s emphasis on employee welfare and health, in order to reduce accidents in the workplace. The originality of this paper lies in its application and validation of a sector-specific safety framework, contributing to the body of knowledge by offering a replicable methodology for adapting safety frameworks to other manufacturing sectors.Safet
Fireside corrosion behavior of thermally sprayed coatings for waste-to-energy power plant applications
Get PDFThis study investigates the fireside corrosion behavior of four (Ni-22Cr, Ni-25Cr, Co-25Cr, and NiCo-25Cr) coatings, which were applied using twin wire arc spray technique and subjected to simulated waste-burning environments (a gas composition containing HCl, SO2, CO2, N2, H2O, balance N2, plus a salt deposit of 50wt.% KCl + 50wt.% K2SO4). The coatings deposited on a conventional base steel alloy (E−250) were tested under these conditions at 550 °C for 500 h in a laboratory-scale atmosphere controlled furnace. After the fireside exposure, the samples were studied using optical microscopy, SEM-EDX, and XRD to deduce coatings performance and possible corrosion mechanisms. The results indicated that all coatings, except Ni-22Cr, outperformed the E−250 steel. The Ni-22Cr and NiCo-25Cr coatings showed similar pitting corrosion behavior with more prominent corrosion pits on Ni-22Cr coating’s surface. The Co-25Cr coating showed slightly improved performance to the above two coatings, which can be attributed to the ability of Co to resist corrosion attack under these conditions. Overall, the Ni-25Cr coating composition was conclusively found to be most effective.Journal of Materials Engineering and Performanc
Strain based finite fracture mechanics for fatigue life prediction of additively manufactured samples
Get PDFA novel failure criterion, named Strain-based Finite Fracture Mechanics, is proposed to predict the fatigue life of additively manufactured notched components under uniaxial loading conditions. The model relies on the simultaneous fulfillment of two conditions: a non-local strain requirement and the discrete energy balance. The inputs of the model are strain and the stress intensity factor at failure, which depend on the number of cycles according to power law equations. The inputs can be obtained based on strain-life and stress intensity factor-life data from plain and notched specimens. The present approach is comprehensively validated against experimental datasets on additively manufactured samples from the literature for different materials, raster angles, notch geometries and loading conditions. Predictions by other approaches, such as Finite Fracture Mechanics (in its original stress formulation) and the Theory of Critical Distances, are also considered, for the sake of completeness. Results show that, in general, the proposed strain-based model is more accurate and provides consistently precise predictions across different cases.This work was funded by HORIZON EUROPE Marie Sklodowska-Curie Actions, 861061International Journal of Fractur
Comparison of PCA and fractal analysis approaches in the evaluation of air-HSR intermodal network
Get PDFThe importance of air transport and high-speed rail (HSR) in building comprehensive transportation systems has grown substantially in recent years. Evaluating the air-HSR intermodal network is essential in identifying the developmental hurdles and charting a course for its progress. This paper compares alternative methods for evaluating the performance of air-high-speed rail (HSR) intermodal networks, with a focus on developing a comprehensive index framework that considers multiple perspectives. Ten Chinese cities with viable air-HSR connectivity are assessed using principal component analysis (PCA) and Fractal Analysis. The study finds that while PCA provides a valuable high-level overview of air-HSR intermodal network integration by identifying major trends and key components, Fractal Analysis offers a complementary and more detailed evaluation by capturing local characteristics and complex spatial interactions. The combined use of PCA and Fractal Analysis ensures a comprehensive assessment, highlighting that Fractal Analysis is particularly effective for evaluating complex intermodal networks when spatial coherence and local variations are critical. The analysis provides decision-makers with a more balanced understanding of the intricate interrelationships between various aspects of the air-HSR intermodal network, which can inform policy decisions related to transportation infrastructure investment and development.Research in Transportation Business & Managemen