27227 research outputs found
Sort by
Signal Recognition and Prediction of Water‐Bearing Concrete Under Axial Compression Using Acoustic Emission and Machine Learning
Get PDFThe presence of free water in the concrete slurry significantly influences the crack patterns of concrete. In this study, uniaxial compression tests were conducted on concrete specimens with varying moisture contents under acoustic emission (AE) monitoring. Through parametric analysis and machine learning, the cracking process of water‐containing concrete was studied, signal patterns during the cracking process were identified, and the impact of moisture content on the damage evolution and fracture mechanism of concrete was understood. The results indicate that free water is capable of absorbing high‐frequency signals. With the increase of moisture content, the AE signals decrease. The failure of concrete is mainly of the tensile type, while the shear‐type accounts for a relatively small proportion. The presence of free water decreases the likelihood of diagonal shear failure in concrete structures. The unsupervised learning was used for various moisture content analyses. Three distinct AE signal patterns were identified during the concrete compression tests: frictional motion signals of the compression surface, fracture surface activity signals, and aggregate cracking signals. Based on the moisture content, this study analyzes the variations in signal responses across different modes. A predictive model was established utilizing the BP neural network to differentiate signals of various modes, achieving an accuracy rate of 99%
Foreign currency forecasting in emerging markets: What can stock, and bond markets tell us?
No full textThis paper provides the first comprehensive investigation on the informational role of financial market information in the profitable predictability of exchange rates in an out-of-sample (OOS) context in emerging markets. Within a comparative analysis framework across developed and emerging countries, we examine if international stock and bond returns can be exploited as a predictor for future spot exchange rate changes (statistical test), and if an economically profitable trading strategy can be executed (economic test). Our central finding is that currency traders can beat emerging markets conditionally on correctly predicting the direction of the OOS forecasted currency returns induced by emerging stock and, to a lesser extent, by bond market returns. By contrast, this profitability is not evident in developed countries data. This asymmetric evidence, on the power of stock and bond returns in the profitable predictability of currency returns across developed and emerging countries, is affected by the country-specific institutional quality
Tackling Grand Challenges: Insights and Contributions From Practice Theories
Get PDFThis curated debate discusses the value of practice theories in studying, understanding and tackling grand challenges. Practice theories assume that social phenomena are constituted through everyday doings and sayings. Building on this premise, the different contributions in this curated debate go beyond the assumption that grand challenges are abstract phenomena. The authors argue that grand challenges are enacted through mundane, situated actions that are often hidden in plain sight. Building on their research, they suggest that understanding grand challenges requires scholars to approach phenomena as nondualistic. Accordingly, they reveal that situated actions are not self-contained but related across space and time, requiring scholars to adopt a relational perspective. The debate concludes with a call for action as we embrace our dual role as scholars and citizens
Experimental analysis of installing multirotor horizontal wind turbines in a ducted wind turbine: The influence of rotor diameter and rotation on power efficiency optimization
Get PDFThe current study focuses on applying duct and multi-rotor wind turbines to enhance the generating capacity of a wind system arrangement in response to the expanding enthusiasm for using renewable energy sources in the municipal area. The outcome of this research can be utilized to introduce optimal turbine arrangements for a range of wind speeds related to specific regions to optimize the amount of power that can be extracted. It can produce power on standalone or in collaboration with other systems, such as Airborne and Invelox configurations. A duct speeds up the wind flow through the turbine location, while additional turbines can capture the remaining energy in the turbine's wake. For this aim, the impact of various configurations of multi-rotor wind turbines mounted on a recently designed duct was explored, followed by an investigation into enhancing the total output power. The effect of rotating direction and rotor diameter has been examined by comparing multiple arrangements to achieve the most significant output power for wind speeds ranging from 4 to 16 m/s. The outcomes prove that in high-speed winds of 12 m/s or more, mounting one rotor with a smaller diameter in the middle of two larger ones within the duct while spinning in the counter-rotating situation enhances the power efficiency by up to 95 %. Moreover, in low-speed winds of 6 m/s or lower, the three rotors with the same diameters presented the highest output, almost 2.1 times compared to the single rotor mounted in the duct throat. Considering an appropriate arrangement for multirotor wind turbines regarding privileged wind speed in the region can significantly increase generated power
Assurance of AI Systems From a Dependability Perspective
Get PDFWe outline the principles of classical assurance for computer-based systems that pose significant risks. We then consider application of these principles to systems that employ Artificial Intelligence (AI) and Machine Learning (ML).
On its own, testing is insufficient for assurance when very high levels of confidence are required. Hence, a key element in the “dependability” perspective is a requirement to have thorough understanding of the internal design and operation (and hence behavior) of critical system components and their interaction. This is considered infeasible for AI and ML because their internal operation is developed experimentally over a limited (albeit large) set of training examples and is opaque to detailed understanding. Hence the dependability perspective, as we apply it here, aims to minimize trust in AI and ML elements by using “defense in depth” with a hierarchy of less complex systems, some of which may be highly assured conventionally engineered components, to “guard” them. This may be contrasted with what we call the “trust-worthiness” perspective that seeks to apply assurance to the AI and ML elements themselves by various forms of careful training, fine tuning, internal “guardrails” and automated examination.
In cyber-physical and many other systems, it is difficult to provide guards that do not depend on AI and ML to perceive their environment (e.g., other vehicles sharing the road with a self-driving car), so both perspectives are needed and there is a continuum or spectrum between them. We focus on architectures toward the dependability end of the continuum and invite others to consider additional points along the spectrum.
For guards that require perception using AI and ML, we examine ways to minimize the trust placed in these elements; they include diversity, defense in depth, explanations, and micro-ODDs (Operational Design Domains). We also examine methods to enforce acceptable behavior, given a model of the world. These include classical cyber-physical calculations and envelopes, and normative rules based on overarching principles, constitutions, ethics, and reputation.
We apply our perspective to autonomous systems, AI systems for specific functions, general-purpose AI such as Large Language Models (LLMs), and Artificial General Intelligence (AGI), and we propose current best practice and conclude with a fourfold agenda for research in which we recommend development and application of: a) new methods for hazard analysis suited to AI systems; b) layered recursively structured architectures for runtime verification and defense in depth; c) assurance for AI-based perception, and d) improved understanding of human and machine cognition, shared intentionality, and emergent behavior
Patient-Reported Importance of Functional Benefit in Geographic Atrophy
Get PDFImportance
Intravitreal complement inhibitors injections (IVCIs) slowed progression of geographic atrophy (GA) lesions in several registration phase 3 trials although without benefit for prespecified secondary functional vision outcomes. Patient acceptability of these therapies needs further exploration.
Objective
To quantify the acceptability of IVCI therapy to United Kingdom patients with GA, assuming vision outcome benefits are expected.
Design, Setting, and Participants
This cross-sectional study took place at 9 geographically dispersed UK National Health Service centers from April 2023 to April 2024 among 153 participants with treatment-naive GA in at least 1 eye.
Exposures
GA in at least 1 eye.
Main Outcomes and Measures
Main outcomes were (1) acceptability of IVCI therapy based on completion of validated acceptability questionnaire. Participants were provided with a treatment information leaflet coproduced by a patients with lived experience of GA to inform them about the risks and benefits of IVCI for GA, assuming there were vision outcome benefits to this treatment and (2) response to the EuroQol 5-dimension with a vision bolt-on questionnaire to assess general health and vision-related quality of life. Spearman rank correlations and χ2 tests were used to explore associations between acceptability levels and specific ocular and sociodemographic characteristics.
Results
A total of 153 participants were recruited (93 [60%] women; mean [SD] age, 82 [7]), 57 (38%) of whom had bilateral foveal involvement. Median (IQR) visual acuity with habitual correction in the better-seeing eye and in eyes where neither eye was better or worse was logMAR, 0.30 (0.14-0.54; approximate Snellen equivalent, 20/40) and 0.47 (0.14-0.84; approximate Snellen equivalent, 20/63), respectively. Among the 153 participants, 81 (53%; 95% CI, 45-61) reported IVCIs were very much or extremely acceptable under the theoretical scenarios provided. The proportion finding IVCIs acceptable rose to 82% (95% CI, 76-88) when including those who rated prospective treatment as moderately acceptable. Belief in the perceived effectiveness of the treatment (ρ, 0.52; 95% CI, 0.40-0.63; P < .001) and confidence in their ability to attend the eye clinic regularly (ρ, 0.51; 95% CI, 0.38-0.62; P < .001) correlated with overall acceptability.
Conclusions and Relevance
IVCI therapy for GA may be acceptable to most UK patients with GA under the assumption that there are vision outcome benefits to this treatment. While current treatments do not result in vision outcome benefits, perceived effectiveness by patients was associated with acceptability, emphasizing the desire to quantify vision functional benefit concomitant with anatomical slowing of progression
Six-year rate of visual field progression in the Laser in Glaucoma and Ocular Hypertension (LiGHT) Trial
Get PDFPurpose
to compare the 6-year rate of visual field (VF) progression in the two arms of the Laser in Ocular Hypertension and Glaucoma Trial (LiGHT), comparing selective laser trabeculoplasty (SLT) and drops as first treatment in ocular hypertension (OHT) and open angle glaucoma (OAG).
Design
post-hoc analysis of data from randomized clinical trial
Subjects
patients with newly diagnosed OHT/OAG recruited in the LiGHT trial.
Methods
in each patient, we selected the better (baseline Mean Deviation, MD) eligible eye with at least 3 reliable VFs (false positive errors < 15%) over at least 6 months. We estimated the rate of MD progression using a published hierarchical linear mixed effect model (LMM), designed to increase precision by minimizing the effect of perimetric learning and test-retest noise. Secondary analyses were performed to assess: the differences in rate across baseline severity groups (OHT, mild OAG and moderate/severe OAG); the effect of glaucoma surgery and switch to SLT in the drops-first arm, by truncating the VF series; the effect of cataract and cataract surgery, by using the Mean Pattern Deviation (MPD) instead of the MD.
Main Outcome Measure
mean difference in the rate of VF MD progression between patients in the SLT-first and drops-first arm.
Results
Data from 710 eyes (482 with OAG, 354 in the SLT-first arm) were analysed. The two arms had similar baseline MD (p=0.7). The average intraocular pressure (IOP) during follow-up was 16.1 [14.2, 18.2] for the drops-first arm and 16.8 [14.6, 18.6] in the SLT-first arm (Median [Interquartile-range], p=0.057). The mean [95%-Credible interval] MD rate was -0.37 [-0.43, -0.31] dB/year in the drops-first arm and -0.26 [-0.31, -0.21] dB/year in the SLT-first arm (p = 0.007). When stratified by severity, this difference was significant only in mild OAG (p = 0.035, the largest sub-group). The secondary analyses largely confirmed the main results. The difference in MPD rate was also significantly slower in the SLT-first arm (p < 0.001).
Conclusions
First-line SLT was more effective than drops at preserving VF. SLT should be preferred as the first line of treatment in newly diagnosed OHT and OAG eyes
High-speed Broadband and Educational Achievements
No full textThis study sheds new light on the short-run effects of access to high-speed internet on educational disparities. By following 3 million students belonging to 6 different cohorts over the period 2012–2022, I estimate the effect of the broadband infrastructure on student performance. While most previous contributions use discontinuous jumps in the available broadband connection speed across space at a given moment in time, this study exploits the gradual rollout of a national infrastructural policy associated with an increase in 30 Mbit/s household broadband coverage from 40% to 80% over a 6-year period. The estimation strategy relies on a unique dataset, combining panel data on student performance with a rich set of school- and student-level information and broadband data measured at a very fine spatial scale. Results show an average null effect of high-speed broadband on 8th grade student performance in both literacy and maths. However, these results mask substantial heterogeneity: low performers in grade 5 and students with more advantaged backgrounds benefit from access to high-speed broadband, whereas the opposite is true for other students. Overall, the findings suggest that access to broadband widened performance disparities across students with different socioeconomic backgrounds
A holistic approach to interpretable modelling and precise forecasting of human mortality rates by gender and country
Get PDFStudies from many countries find that gender differences in mortality rates and life expectancy vary by country. The multipopulation Lee-Carter family of models, a widely-used methodology, decompose mortality rates into age, time, and country components, offering valuable insights into mortality trends. We delve into the interpretability of the Lee-Carter multipopulation model, elucidating its ability to capture underlying mortality patterns and project future trajectories. Moreover, we extend our analysis by incorporating machine learning techniques to model the residuals of the Lee-Carter framework. The main contribution of the paper is to introduce these techniques in the context of the multiple population mortality models. Specifically, we employ Random Forest to refine joint mortality forecasts by country, effectively capturing complex nonlinear relationships in residuals and improving predictive performance.
In this paper, we revisit these models using new statistical techniques and data sets from the Human Mortality Database. By leveraging advanced computational algorithms, we aim to enhance the accuracy of mortality rate predictions and account for residual patterns that may not be captured by the traditional Lee-Carter approach alone. Through empirical validation and comparative analyses, we demonstrate the efficacy of integrating machine learning into multiple population mortality forecasting, thereby contributing to the refinement and improvement of mortality modeling methodologies
Planning in Nature’s Metropolis: Metabolic Municipalism and Ecological Planning in Barcelona
Get PDFDemocratic economic planning is emerging once again after decades of marginalisation. This article contributes to the ecological turn in the new economic planning literature by attending to new municipalist approaches to repairing metabolic rifts opened by capitalist urbanisation. It presents a qualitative study of the office of strategic planning for the Barcelona metropolitan region (PEMB) to examine how questions of social metabolism have informed its revaluation of planning, situating these changes within what we identify as an incipient ‘metabolic municipalism’. By examining how PEMB has redefined ‘the economic’ in economic planning, and how it has worked around the challenges of distributed planning without power, through public-community partnerships, we aim to illuminate and critically assess the elements of an ecological planning for metabolic sovereignty in conditions of planetary urbanisation
Access Repository Dashboard
Do you manage City Research Online? Access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard!