Abstract Managed retreat, the purposeful relocation of households and assets to reduce flood risk, is gaining recognition as an essential adaptation strategy under intensifying climate change. Although often contested and perceived as socially or politically unacceptable, managed retreat holds potential to enhance the long‐term resilience of at‐risk communities. In Europe, however, it remains comparatively underexplored, with only a handful of European managed retreat cases that have been reported on in the academic literature. Here, we present a data set of European managed retreat cases, based on a multilingual review of academic and gray literature, as well as media articles. We found 44 implemented or planned cases of managed retreat across the continent, spanning 11 countries, ranging from the relocation of individual assets to more than 1,500 households. Through a cross‐case analysis, we identify five key factors that influence the process and outcomes of managed retreat projects: the compensation offered, the timing of the project, the engagement of the affected community, the leadership taken by the government, and the post‐relocation land use. Our analysis demonstrates that, although managed retreat remains less common than engineered protection measures, it is more prevalent in Europe than previously assumed and is already being practiced in varied forms. By uncovering common challenges and enabling conditions, this study offers transferable insights for advancing more anticipatory and strategically designed managed retreat initiatives, both within Europe and beyond.
The phenomenon that multi-path components (MPCs) arrive in clusters has been verified by channel measurements, and is widely adopted by cluster-based channel models. As a crucial intermediate processing step, MPC clustering bridges raw data in channel measurement and cluster characteristics for channel modeling. In this paper, a physical-interpretable and self-adaptive MPC clustering algorithm is proposed, which can locate both single-point and wide-spread scatterers without prior knowledge. Inspired by the concept in geography, a novel metaphor that interprets features of MPC attributes in the power-delay-angle profile (PDAP) as topographic concepts is developed. In light of the interpretation, the proposed algorithm disassembles the PDAP by constructing contour lines and identifying characteristic points that indicate the skeleton of MPC clusters, which are fitted by analytical models that associate MPCs with physical scatterer locations. Besides, a new clustering performance index, the power gradient consistency index, is proposed. Calculated as the weighted Spearman correlation coefficient between the power and the distance to the center, the index captures the intrinsic property of MPC clusters that the dominant high-power path is surrounded by lower-power paths. The performance of the proposed algorithm is analyzed and compared with the counterparts of conventional clustering algorithms based on the channel measurement conducted in an outdoor scenario. The proposed algorithm performs better in average Silhouette index and weighted Spearman correlation coefficient, and the average root mean square error (RMSE) of the estimated scatterer location is 0.1 m.
Onel Pérez-Fernández, Octavio Quintero Ávila, Carolina Barros
et al.
In Latin American cities, violence against women (VAW) remains critical for public health, well-being, and safety. This phenomenon is influenced by social, political, and environmental drivers. VAW is not randomly distributed; built environments—geography, ambient population, and street networks—influence criminal through spatial dependence across multiple scales. Despite growing interest in the spatial distribution of crime, few studies have explicitly explored the spatiotemporal dimensions of VAW in Monterrey. This study explores spatio-temporal patterns of VAW in Monterrey, Mexico, based on the analysis of 27,036 georeferenced and verified emergency reports from the 911 system (2019–2022). The study applies kernel density estimation (KDE), the Getis–Ord G<sub>i</sub>* statistics, the Local Moran I index, and space–time cube analysis to identify spatial and temporal clusters of VAW. The results show concentrations of incidents during nighttime and weekends, particularly in northern and eastern sectors in Monterrey. The analysis reveals clusters in areas of high socioeconomic vulnerability. VAW in Monterrey follows predictable and cyclical patterns. These insights contribute to the design of tailored public policies and actions to improve women’s health, well-being, and safety in critical zones and timeframes. The findings also enhance international understanding of gender-based spatial violence patterns in the rapidly urbanizing contexts of the Global South.
Guided by the Einstein equivalence principle that identifies the phenomenon of gravitation as a manifestation of the dynamics of spacetime in contrast to a localizable force, we review and explore its consequences on formulating a theory of gravity. The resulting space of metric theories of gravity may address open conceptual and observational puzzles through a wealth of effects beyond general relativity, whose traces can be searched for within today's and tomorrow's gravitational testing grounds. Above all, we offer a generic metric theory generalization of Isaacson's approach to the leading-order field equations of physical perturbations with a well-defined notion of energy-momentum carried by the gravitational waves. Within this framework, we identify the backreaction of the Isaacson energy-momentum flux onto the background spacetime with the displacement memory effect that induces a permanent distortion of space after the passage of a gravitational wave. This effect is a well-known prediction of GR whose dominant contribution captures its inherent non-linear nature, manifest in the ability of gravity to gravitate. However, the novel interpretation of memory as naturally arising within the Isaacson approach to gravitational waves comes with two main advantages. Firstly, it allows for a unified understanding of both the null and the ordinary memory effect, which are respectively sourced by unbound energy fluxes that do and do not reach asymptotic null infinity. Secondly, and most importantly, this approach allows for a consistent derivation of the memory formula for a large class of metric theories with considerable lessons to be learned for upcoming future measurements of the memory effect.
Most successes in autonomous robotic assembly have been restricted to single target or category. We propose to investigate general part assembly, the task of creating novel target assemblies with unseen part shapes. As a fundamental step to a general part assembly system, we tackle the task of determining the precise poses of the parts in the target assembly, which we we term ``rearrangement planning''. We present General Part Assembly Transformer (GPAT), a transformer-based model architecture that accurately predicts part poses by inferring how each part shape corresponds to the target shape. Our experiments on both 3D CAD models and real-world scans demonstrate GPAT's generalization abilities to novel and diverse target and part shapes.
This dissertation is based on a project co-founded by the Health Market Quality Program (now Rozetta Institute) and the Australian Institute of Health and Welfare. The overall objective of this work is to provide a framework and a tool for classification and clustering of homogeneous geographic areas based on aggregated population data. Thus, to enable the presentation and reporting of comparable information of individual units with peers, I develop the Homogeneity and Location indices to measure respectively the dispersion and central tendency of a categorical ordinal distribution. The advantages of such indices include statistical efficiency and a simple presentation of results. Our approach is founded on the general theory of probability distributions, and our aim is to provide a natural benchmark for a homogeneity measure in terms of what is a "high" and "low" concentration of a probability distribution. Currently, there is no accepted benchmark that could be used to assess the homogeneity of a categorical ordinal variable. In this work, the proposed statistical indices are used to assess the socioeconomic homogeneity of the commonly used SA3 Australia census geography and analyse the variation of GP attenders in the metropolitan area of Sydney. The approach can be used to classify any geographic area and explore variation across any specified geographical boundaries. The SA3 dataset and scripts (R/Python) to develop these indices have been made available on my GitHub account: https://github.com/lpinzari/homogeneity-location-index
Cláudio Luis de Araújo Neto, Daniel Epifânio Bezerra, Laércio Leal dos Santos
et al.
A disposição dos Resíduos Sólidos Urbanos (RSU) constitui uma das principais problemáticas da sociedade moderna, abrangendo aspectos econômicos, sociais e ambientais. Diante desse contexto, este trabalho tem por objetivo avaliar o potencial econômico dos resíduos passivos para a reciclagem na cidade de Campina Grande - PB. A metodologia deste trabalho foi segmentada em três etapas. A primeira etapa compreendeu o levantamento de dados da cidade de Campina Grande - PB. A segunda etapa abrangeu a caracterização gravimétrica dos resíduos sólidos urbanos que são gerados em Campina Grande e depositados no aterro sanitário. E na terceira etapa houve o processamento das informações obtidas nas etapas anteriores para analisar o potencial econômico dos resíduos recicláveis. Os resultados obtidos demonstraram que os resíduos sólidos urbanos gerados em Campina Grande e destinados para o aterro sanitário possuem um potencial econômico considerável, tendo em vista que 86 toneladas de resíduos passíveis de reciclagem são encaminhados ao aterro sanitário e poderiam gerar uma receita de R$ 25.956.000,00 ao ano.
The adoption and diffusion of innovations are essential for both the development of production processes and the improvement of agricultural environmental sustainability, at any stage of the value chain. In recent years, social scientists have studied the diffusion and adoption of agricultural innovations from different approaches, such as innovation diffusion theory, behavioral models, econometric models, social capital and social network analysis, among others. In this study we analyze the scientific literature through a bibliometric analysis based on co-citation networks, to explore the theoretical pillars and bibliographic coupling, with which we explore the current methodological research trends of the last 50 years. The conclusions drawn from this analysis are that in recent years agricultural researchers on adoption and diffusion have designed multivariate methods that combine diverse study approaches. This review contributes to a better understanding of theory and practice in the study of the adoption and diffusion of agricultural innovations.
The positive mass theorem in general relativity states that in an asymptotically flat spacetime, if the momentum--energy tensor is divergence-free and satisfies a dominant energy condition, then a total momentum--energy four-vector can be formed, of which the energy component is nonnegative. In this paper, we take the wave four-tensor of a plane light wave in free space as a counterexample to show that there is no guarantee that a total four-vector can be formed. Thus the theoretical framework for the positive mass theorem is flawed. In addition, it is also shown as well that the Lorentz covariance of Dirac wave equation is not compatible with Einstein mass--energy equivalence.
Okello Ochieng Phillip, Tan Guirong, Ongoma Victor
et al.
Convectively coupled equatorial Kelvin waves (CCEKWs) are those types of equatorially trapped disturbances that propagate eastward and are among the most common intra-seasonal oscillations in the tropics. There exists two-way feedback between the inter-tropical convergence zone (ITCZ) and these equatorially trapped disturbances. Outgoing Longwave Radiation (OLR) was utilized as a proxy for deep convection. For CCEKWs, the modes are located over the West Atlantic, equatorial West Africa, and the Indian Ocean. The influence of other circulations and climate dynamics is studied for finding other drivers of climate within East Africa. The results show a positive relationship between Indian and Atlantic Oceans Sea Surface Temperatures and March-May rainfall over equatorial East Africa over the period of 1980 to 2010. This influence is driven by the Walker circulation and anomalous moisture influx enhanced by winds. Composite analysis reveals strong lower-tropospheric westerlies during the active phase of the CCKWs activities over Equatorial East Africa. The winds are in the opposite direction with the upper-tropospheric winds, which are easterlies. Singular Value Decomposition shows a strong coupling interaction between rainfall over equatorial East Africa and CCKWs. This study concludes that Kelvin waves are not the main factors that influence rainfall during the rainy season. Previous studies show that the main influencing factors are ITCZ, El-Nino Southern Oscillation (ENSO), and tropical anticyclones that borders the African continent. However, CCKWs are a significant factor during the dry seasons.
ethnicity inevitably mingles with other discussions such as those on race, gender and social mobility, and because the book aims to give a general overview each case mentioned in the book receives relatively limited space. In addition to the complexity of ethnicity as witnessed on the ground, Kaplan also rightly reminds readers that spatial concentration and placemaking can be a product of voluntary or involuntary choices by ethnic groups, even though the line between the two can be blurry. When it comes to evaluating the impacts of ethnic concentration and placemaking, he likewise reminds readers that positive and negative outcomes of segregation are relational, and we should not overlook the heterogeneity of an ethnic minority group. The book is easy to follow and explains ethnicity and spatial manifestation in a nonacademic style, so it should appeal to an audience are new to the study of ethnicity and geography. It fulfills the goal set out in the first chapter of untangling the causes of ethnic concentration and segregation and explaining how these geographies are made manifest, along with the consequences of such spatial separation (p. 18). Given the complexity of the topic, this book has done a great job of providing key information and describing relevant debates on ethnicity in human geography, and for that reason can be recommended as a starting point that will lead interested readers to other, more in-depth readings and relevant texts on ethnicity.
Griffin Mooers, Mike Pritchard, Tom Beucler
et al.
We explore the potential of feed-forward deep neural networks (DNNs) for emulating cloud superparameterization in realistic geography, using offline fits to data from the Super Parameterized Community Atmospheric Model. To identify the network architecture of greatest skill, we formally optimize hyperparameters using ~250 trials. Our DNN explains over 70 percent of the temporal variance at the 15-minute sampling scale throughout the mid-to-upper troposphere. Autocorrelation timescale analysis compared against DNN skill suggests the less good fit in the tropical, marine boundary layer is driven by neural network difficulty emulating fast, stochastic signals in convection. However, spectral analysis in the temporal domain indicates skillful emulation of signals on diurnal to synoptic scales. A close look at the diurnal cycle reveals correct emulation of land-sea contrasts and vertical structure in the heating and moistening fields, but some distortion of precipitation. Sensitivity tests targeting precipitation skill reveal complementary effects of adding positive constraints vs. hyperparameter tuning, motivating the use of both in the future. A first attempt to force an offline land model with DNN emulated atmospheric fields produces reassuring results further supporting neural network emulation viability in real-geography settings. Overall, the fit skill is competitive with recent attempts by sophisticated Residual and Convolutional Neural Network architectures trained on added information, including memory of past states. Our results confirm the parameterizability of superparameterized convection with continents through machine learning and we highlight advantages of casting this problem locally in space and time for accurate emulation and hopefully quick implementation of hybrid climate models.
We study the theoretical properties and counterfactual predictions of a large class of general equilibrium trade and economic geography models. By combining aggregate factor supply and demand functions with market-clearing conditions, we prove that existence, uniqueness, and—given observed trade flows—the counterfactual predictions of any model within this class depend only on the demand and supply elasticities (“gravity constants”). Using a new “model-implied” instrumental variables approach, we estimate these gravity constants and use these estimates to compute the impact of a trade war between the United States and China.
The Murray-Darling Basin, in south-eastern Australia, comprises 14 per cent of Australia’s geography. This paper examines some of the historical and contemporary discourses that have been deployed in the last 120 years in managing the complex challenges of the Basin. Differently to prior Indigenous practices, prevailing environmental discourses in this period have highlighted the disconnect between humans and their environment. Whilst Ecologically Sustainable Development underpins the objects of the Water Act 2007 (Cth), it is evident that, in fact, it is an economic rationalism discourse that has been deployed to regulate environmental outcomes through the marketisation of water rights.
Law, Law in general. Comparative and uniform law. Jurisprudence
The AGINAO is a project to create a human-level artificial general intelligence system (HL AGI) embodied in the Aldebaran Robotics' NAO humanoid robot. The dynamical and open-ended cognitive engine of the robot is represented by an embedded and multi-threaded control program, that is self-crafted rather than hand-crafted, and is executed on a simulated Universal Turing Machine (UTM). The actual structure of the cognitive engine emerges as a result of placing the robot in a natural preschool-like environment and running a core start-up system that executes self-programming of the cognitive layer on top of the core layer. The data from the robot's sensory devices supplies the training samples for the machine learning methods, while the commands sent to actuators enable testing hypotheses and getting a feedback. The individual self-created subroutines are supposed to reflect the patterns and concepts of the real world, while the overall program structure reflects the spatial and temporal hierarchy of the world dependencies. This paper focuses on the details of the self-programming approach, limiting the discussion of the applied cognitive architecture to a necessary minimum.
Nicholas C. Stone, Michael Kesden, Roseanne M. Cheng
et al.
A tidal disruption event (TDE) ensues when a star passes too close to the supermassive black hole (SMBH) in a galactic center and is ripped apart by the tidal field of the SMBH. The gaseous debris produced in a TDE can power a bright electromagnetic flare as it is accreted by the SMBH; so far, several dozen TDE candidates have been observed. For SMBHs with masses above $\sim 10^7 M_\odot$, the tidal disruption of solar-type stars occurs within ten gravitational radii of the SMBH, implying that general relativity (GR) is needed to describe gravity. Three promising signatures of GR in TDEs are: (1) a super-exponential cutoff in the volumetric TDE rate for SMBH masses above $\sim 10^8 M_\odot$ due to direct capture of tidal debris by the event horizon, (2) delays in accretion disk formation (and a consequent alteration of the early-time light curve) caused by the effects of relativistic precession on stream circularization, and (3) quasi-periodic modulation of X-ray emission due to global precession of misaligned accretion disks and the jets they launch. We review theoretical models and simulations of TDEs in Newtonian gravity, then describe how relativistic modifications give rise to these proposed observational signatures, as well as more speculative effects of GR. We conclude with a brief summary of TDE observations and the extent to which they show indications of these predicted relativistic signatures.