Search Results (427)

This paper reviews, analyses, and suggests practical mitigation techniques at source for reducing vibration-induced annoyance to occupants in building structures that are built on top of significant railway infrastructure. The dynamic characteristics of vibration caused by wheel-rail interaction at metro train depots are different from those on main-lines and conventional studies. Ground-borne vibration in a building directly above a double-deck railway depot was investigated, focusing on vibration attenuation through rail track design, which is more effective and economic compared to treatments at receivers or along prorogation paths. A 2.5-Dimensional finite element model was established to simulate vibration transmission using different combinations of track-forms. Source contribution under different train running conditions has been evaluated by computing vibration levels along the main transmission path. Vibration levels at representative positions in the building rooms have been predicted using the numerical model and have been compared against site measurements at the corresponding locations after the completion of the construction of the depot and buildings. It was found that the 2.5D FE model enables a reasonable prediction of ground-borne vibration from the metro depot, and that by appropriate design of the track-form, a good level of vibration attenuation can be achieved in an economical way. Full article

Identifying areas that frequently experience post-rainfall ponding is essential for effective flood mitigation and planning. This study integrates Sentinel-1 radar imagery and the Topographic Control Index (TCI) to identify 378 flood-prone urban depressions in Beaumont, Texas. Out of 159 major rainfall events, only six had Sentinel-1 radar imagery acquired within six hours of peak rainfall, and these were used to generate the flood frequency map; the ground-based flood sensor data were used to verify that these selected events corresponded to actual peak rainfall and to validate radar-detected water pixels. Validation results showed 100% precision, 70.87% recall, an F1-score of 82.95%, and 71.32% overall accuracy. Approximately 84% of medium-to-high TCI depressions overlapped with Beaumont’s two-year inundation map, confirming a strong relationship between TCI and observed flooding. A total of 124 depressions retained significant water, and after excluding 25 engineered detention ponds, 99 natural depressions remained flood vulnerable. Among these, 74 depressions with medium or high TCI were identified as the highest-priority nuisance flooding hotspots. The results demonstrate that combining TCI with radar imagery provides a reliable and cost-effective approach for identifying areas prone to frequent urban ponding. This framework supports practical decision-making for drainage improvements, hotspot identification, and early-warning system development in urban flood-prone regions. Full article

Domestic cats are valued companions for many people, but when they free-roam, they can pose risks to biodiversity, communities, and their own welfare. Increasing cat containment has become a priority in Australia, yet shifting owner practices requires overcoming behavioural and structural barriers. The Keeping Cats Safe at Home (KCSAH) project was a four-year, AUD 2.5 million initiative delivered by the Royal Society for the Prevention of Cruelty to Animals New South Wales (RSPCA NSW) from 2021 to 2024, trialling human behaviour change strategies to reduce the impacts of roaming cats in 11 NSW local government areas. Grounded in social science research, the project combined social marketing campaigns, educational resources, school programmes, and community events with subsidised desexing. The project achieved substantial reach, engaging more than 3.5 million people via social media, 42,000 through blogs, 87,000 via the website, and 36,000 through community events. Over 2700 cats were desexed and 1700 microchipped. Ecological monitoring showed reductions in free-roaming cat densities in three council areas, with many also recording declines in nuisance complaints and impoundments. Caregivers exposed to campaign messaging reported greater capability, opportunity, and motivation to contain cats; however, methodological constraints limited the ability to assess actual behaviour change. KCSAH demonstrates the opportunities and challenges of large-scale cat management, highlighting the importance of tailored interventions, veterinary desexing capacity, and nationally consistent monitoring frameworks. Full article

Considering the prevalence of migraine and its impact on everyday living, its evolutionary persistence remains puzzling. This essay reviews recent literature and conceptual perspectives that frame migraine attacks as a possible side-effect of prolonged stress and unmet needs. To illustrate this, the article compares the antithetical relationship of triggers and migraine symptoms: During the early phase of the attack, many eat, drink, rest and sleep more and tolerate less nuisance compared to the hours and days before; previously, however, there was too little time to eat, drink, rest, and sleep, and the nuisance had to be tolerated. A relevant characteristic of many migraineurs is that they are prone to stress, e.g., because of a character trait, an impaired adaptation to stress, the lack of habituation to sensory stimuli, and disturbances of the energy supply. In that way, the appearance of the attack during fading stress makes sense: the body seizes the opportunity and communicates its needs when circumstances permit. In this context, the concept of pain as an imperative—a signal designed to enforce behavioural change—provides an insightful framework. Understanding migraine in this way may help reframe its pathophysiology and its clinical and translational significance. Full article

Ecosystems worldwide are being influenced by climate change in complex ways, leading to profound impacts on biodiversity. While these shifts may constrain the adaptive capacity of some species, they may simultaneously promote the expansion of others, including certain rodents. The Funambulus pennantii (five-striped northern palm squirrel) and Funambulus palmarum (three-striped palm squirrel) demonstrate exceptional adaptability across diverse habitats from rural plantations to densely populated urban areas. Their close association with humans ranges from causing crop damage to becoming urban nuisances, leading to their broad classification as agricultural pests. Hence, this study utilizes ensemble species distribution models to identify the climatic niches of these two species and delineate overlapping suitable habitats within agricultural zones in current and different future climate scenarios. The ensemble model identified 215,748 km² of suitable habitat for F. pennantii and 39,578 km² for F. palmarum under current climatic conditions in India. The future projections indicate habitat increases of about 20.6% for F. pennantii and 48.1% for F. palmarum. The agricultural overlap is also projected to rise by up to 45% and 48%, respectively, compared with present overlaps of 215,595 km² and 39,073 km². The most substantial expansions are projected in the Gangetic Plains, Central Highlands, and parts of the Western and Eastern Ghats and Deccan Plateau. These findings suggest that both species possess high resilience to environmental change and may pose increasing risks to agriculture in a warming climate. The study underscores the need for proactive, ecologically sustainable management strategies to mitigate potential human–squirrel interactions and agricultural losses, offering a foundation for targeted regional interventions. Full article

We develop a hybrid framework for quantum parameter estimation in the presence of nuisance parameters. In this scheme, the parameters of interest are treated as fixed non-random parameters while nuisance parameters are integrated out with respect to a prior (random parameters). Within this setting, we introduce the hybrid partial quantum Fisher information matrix (hpQFIM), defined by prior-averaging the nuisance block of the QFIM and taking a Schur complement, and derive a corresponding Cramér–Rao-type lower bound on the hybrid risk. We establish the structural properties of the hpQFIM, including inequalities that bracket it between computationally tractable approximations, as well as limiting behaviors under extreme priors. Operationally, the hybrid approach improves over pure point estimation since the optimal measurement for the parameters of interest depends only on the prior distribution of the nuisance, rather than on its unknown value. We illustrate the framework with analytically solvable qubit models and numerical examples, clarifying how partial prior information on nuisance variables can be systematically exploited in quantum metrology. Full article

Consider the dynamical system x ˙ = f ( x ) , where x ∈ R n is the state vector, x ˙ is the time or spatial derivative, and f is the system model. We wish to identify unknown f from its time-series or spatial data. For this, we propose a Bayesian framework based on the maximum a posteriori (MAP) point estimate, to give a generalized Tikhonov regularization method with the residual and regularization terms identified, respectively, with the negative logarithms of the likelihood and prior distributions. As well as estimates of the model coefficients, the Bayesian interpretation provides access to the full Bayesian apparatus, including the ranking of models, the quantification of model uncertainties, and the estimation of unknown (nuisance) hyperparameters. For multivariate Gaussian likelihood and prior distributions, the Bayesian formulation gives a Gaussian posterior distribution, in which the numerator contains a Mahalanobis distance or “Gaussian norm”. In this study, two Bayesian algorithms for the estimation of hyperparameters—the joint maximum a posteriori (JMAP) and variational Bayesian approximation (VBA)—are compared to the popular SINDy, LASSO, and ridge regression algorithms for the analysis of several dynamical systems with additive noise. We consider two dynamical systems, the Lorenz convection system and the Shil’nikov cubic system, with four choices of noise model: symmetric Gaussian or Laplace noise and skewed Rayleigh or Erlang noise, with different magnitudes. The posterior Gaussian norm is found to provide a robust metric for quantitative model selection—with quantification of the model uncertainties—across all dynamical systems and noise models examined. Full article

Honey adulteration has long been a nuisance in local and international trade. Sugar syrup addition and false labeling of botanical origin have created a challenge in identifying fraudulent honey supplies and products. Stable carbon isotope ratio analysis (SCIRA) has been widely employed in honey authentication. While it is effective in identifying the addition of C4 plant-derived sugars, it does not provide information related to honey’s botanical source. This research investigated the combination of SCIRA and melissopalynology to provide a more robust assessment of honey integrity and showed that PCA analysis of δ¹³C together with sugar profiles could further improve the decision involving addition of sugar syrups. A total of 34 beekeeper honey samples were analyzed from 7 provinces of Thailand with a focus on longan honey. Twenty-four samples passed the δ¹³C criteria, exhibiting δ¹³C of bulk honey ranging from −28.53 ± 0.19‰ to −22.89 ± 0.08‰ and δ¹³C of extracted protein ranging from −29.30 ± 0.07‰ to −22.76 ± 0.03‰. Pollen profiling further eliminated honey of questionable and multifloral origins, yielding only eight samples that passed both criteria of being monofloral and not being adulterated with C4-derived sugars. These included six samples of longan honey and two honey samples of other botanical origins, yielding an overall passing rate of 23.5%. Our study showed that by combining SCIRA and melissopalynology, a robust determination of honey integrity could be achieved. Full article

An extended growth curve model with fixed and random effects is considered. Under the assumption of multivariate normality, the maximum likelihood estimators of the fixed effects and the dispersion matrix are determined in a model with random nuisance parameters, both without any assumption on the covariance structure and under the assumption of compound symmetry. For this purpose, rules for differentiation of symmetric matrices are applied. Furthermore, when the experiments are designed in balanced complete blocks, particular symmetric matrices appear in the likelihood equations, allowing closed-form expressions for the estimators. It is also shown that the vector of sufficient statistics for the fixed effects extended growth curve model is also sufficient for the model with random nuisance parameters. The presented results are illustrated using a real data example. Full article

Rapid urban expansion and increasing population density intensify the loss of open spaces, exacerbate flooding frequency and runoff pollution, increase the urban heat island effect, and deteriorate ecological resilience and human well-being. This study presents Gazelle Valley Park (GVP) in Jerusalem (Israel), a unique large-scale ecohydrological infrastructure within a dense Mediterranean city. GVP was established in 2015 following a public-led campaign and comprises a multifunctional nature-based solution designed to collect and circulate stormwater through a series of vegetated ponds, enhancing filtration, aeration, and pollutant removal, while sustaining a wetland ecosystem. Its design follows international ecological standards and embodies the principle “from nuisance to resource”, transforming urban runoff into an asset that supports rich biodiversity while offering recreational, cultural, and educational activities. During the dry summer, reclaimed wastewater is introduced in order to support a perennial aquatic habitat, which introduces various challenges due to increased salinity, oxygen demand, and contaminants. Hydrometric and geochemical monitoring demonstrates strong correlations between rainfall and runoff and point at the role of sedimentation and vegetation in reducing pollutant loads. The park benefits from its holistic operation, where hydrology, ecology, education, and public engagement are integrated, thus making the whole greater than the sum of its parts. Full article

A statistical manifold M can be defined as a Riemannian manifold each of whose points is a probability distribution on the same support. In fact, statistical manifolds possess a richer geometric structure beyond the Fisher information metric defined on the tangent bundle $TM$. Recognizing that points in M are distributions and not just generic points in a manifold, $TM$ can be extended to a Hilbert bundle $HM$. This extension proves fundamental when we generalize the classical notion of a point estimate—a single point in M—to a function on M that characterizes the relationship between observed data and each distribution in M. The log likelihood and score functions are important examples of generalized estimators. In terms of a parameterization $\theta :M\to \mathrm{\Theta }\subset {\mathbb{R}}^k$, $\widehat{\theta }$ is a distribution on $\mathrm{\Theta }$ while its generalization $g_{\widehat{\theta }}=\widehat{\theta }-E\widehat{\theta }$ as an estimate is a function over $\mathrm{\Theta }$ that indicates inconsistency between the model and data. As an estimator, $g_{\widehat{\theta }}$ is a distribution of functions. Geometric properties of these functions describe statistical properties of $g_{\widehat{\theta }}$. In particular, the expected slopes of $g_{\widehat{\theta }}$ are used to define $\mathrm{\Lambda }\left(g_{\widehat{\theta }}\right)$, the $\mathrm{\Lambda }$-information of $g_{\widehat{\theta }}$. The Fisher information I is an upper bound for the $\mathrm{\Lambda }$-information: for all g, $\mathrm{\Lambda }\left(g\right)\le I$. We demonstrate the utility of this geometric perspective using the two-sample problem. Full article

The water deer, although an internationally endangered species, is designated as a nuisance wild animal in South Korea and occupies a unique ecological niche. Studying the gut microbiome of this species is crucial for understanding its ecology. We amplified 16S rRNA DNA and compared the gut microbiomes of wild water deer from three regions with those of captive water deer from one region. Our results showed that the gut microbiome diversity of water deer did not differ significantly across regions in the wild but decreased significantly when raised in captivity. The similar microbiomes of water deer living in different regions are believed to be due to dietary diversity rather than dietary homogeneity. Furthermore, the monotony of the food supply appears to lead to significant variation in captive environments. From a conservation biology and biorestoration perspective, we suggest the importance of conserving the gut environments of animals conserved and restored outside their native habitats. Full article

Rapid decarbonization relies on knowing which structural and energy factors affect national carbon dioxide emissions. Much of the literature leans on linear and additive assumptions, which may gloss over curvature and interactions in this energy–emissions link. Unlike previous studies, we take a different approach. Using a panel of 80 high- and upper-middle-income countries from 2011 to 2020, we model emissions as a function of fossil fuel energy consumption, methane, the food production index, renewable electricity output, gross domestic product (GDP), and trade measured as trade over GDP. Our contribution is twofold. First, we evaluate how different modeling strategies, from a traditional Generalized Linear Model to more flexible approaches such as Support Vector Machine regression and Random Forest (RF), influence the identification of emission drivers. Second, we use Double Machine Learning (DML) to estimate the incremental effect of fossil fuel consumption while controlling for other variables, offering a more careful interpretation of its likely causal role. Across models, a clear pattern emerges: GDP dominates; fossil fuel energy consumption and methane follow. Renewable electricity output and trade contribute, but to a moderate degree. The food production index adds little in this aggregate, cross-country setting. To probe the mechanism rather than the prediction, we estimate the incremental role of fossil fuel energy consumption using DML with RF nuisance functions. The partial effect remains positive after conditioning on the other covariates. Taken together, the results suggest that economic scale and the fuel mix are the primary levers for near-term emissions profiles, while renewables and trade matter, just less than is often assumed and in ways that may depend on context. Full article

This study intends to identify and quantify the individual, perceptual, and contextual factors associated with odor-related perception and to assess the perception of odor sources according to meteorological conditions. Two face-to-face seasonal community surveys were conducted using stratified random sampling with proportional allocation, yielding representative samples of residents in a southern Brazilian city, where mild constant temperatures throughout the year and shifting prevailing wind directions expose residents to different odor sources. Chi-Square tests were applied to assess associations between odor perception and qualitative variables, while logistic regression was used to identify predictors of higher annoyance. Results showed that prevailing wind direction influenced source attribution, with steel industry and sewage-related sites most frequently cited. Proximity to the steel plant increased both source recognition and annoyance levels. Reported impacts included closing windows and reducing outdoor activities. Self-reported respiratory problems consistently predicted higher annoyance levels in both surveys. The statistical methods were effective in analyzing the likelihood of odor-related perception and its relationship with explanatory variables. These findings highlight the value of a data-driven approach—specifically, integrating wind direction, source proximity, and community-based perception—to support urban environmental management and guide odor mitigation strategies. Full article

The sustainable transformation of areas associated with mining is an essential contemporary challenge. In the course of such transformations, economic benefits are confronted with community criticism of heavy industry. In this context, the study examines spatial solutions implemented in the revitalisation of areas adjacent to active industrial sites. The article aims to characterise solutions applied in locations that elude a straightforward division into industrial and post-industrial. The motivations of the entities involved in the construction and the effects of implementing such projects are investigated. To achieve this aim, compositional and visual linkages in four locations (in Germany and Poland) were analysed, along with the intentions of designers and investors and the opinions of users. The study revealed the influence of political decisions on spatial solutions, an aspect not previously analysed, which has led to a limited understanding of the role they play in the transformation. It was indicated that drawing users’ attention to the aesthetic values of active industrial areas coincides with diverting attention from their nuisances. The discreet cooperation between local authorities, designers, and industry (as expressed in architectural solutions) was emphasised. The research opens a field for discussion on managing community perceptions through spatial solutions. Full article