Search Results (119)

Packet delivery in vehicular ad hoc networks degrades under realistic road dynamics, where mobility and local density vary over time and across road layouts. This study revisits route lifetime control in AODV and introduces Vehicular Traffic Condition-Based AODV, which adjusts the Active Route Timeout and the Delete Period Constant online at each HELLO reception using locally observable cues on neighbor density and short-term speed variation. The design is empirically informed by OpenStreetMap and SUMO mobility with OMNeT++/Veins/INET co-simulation. The analysis highlights two recurrent patterns that guide the method: (i) an intermediate neighbor-density range—roughly from the mid-teens to about twenty neighbors—where average speed tends to vary more rapidly; and (ii) a distribution of short-term speed-change magnitudes, sampled at the instants of HELLO reception, that is concentrated within a narrow interval with a light upper tail. Accordingly, the proposed method increases or decreases route-entry lifetimes with heightened responsiveness inside this density range, while applying conservative updates elsewhere to mitigate oscillations. Evaluation across multiple vehicular-traffic conditions spanning three fleet sizes (200, 300, 400 vehicles) and three speed-limit settings (10, 20, 30 km/h) demonstrates consistent packet delivery ratio gains over conventional AODV and close tracking of the best static lifetime configurations identified per condition. The gains are attributable to timely pruning of unstable paths and sustained retention of stable paths, which increases valid forwarding opportunities without centralized coordination. Full article

In this paper, climate evolution is revisited in terms of the theory of dynamical systems, which has been successfully used in predictions of catastrophic events such as avalanches, landslides, or economy and civilization collapses. Such tipping events are announced by warning signs, named “pre-critical fluctuations” or “critical softening”, allowing a tipping date estimate through well-known equations. In the case of climate, the warning signs are extreme events of increasing amplitudes. We show that in such a context, numerical simulations can hardly predict incoming tipping points, due to a divergence in computational time at the singularity. Based on the dynamical systems theory, a recent publication from Copenhagen University shows that the Atlantic Meridional Oceanic Circulation is likely to collapse well before the end of the century, triggering switchover cascades, eventually culminating in global climate tipping. Paleoclimatic studies also show that tipping events occurred in the past, particularly during the PETM period 56 Myrs ago. If this was to happen now, average global temperatures might reach an unbearable level, with a deadline much closer than expected. This extreme emergency has major consequences on the implementation times of sustainability policies and in energy production, mobility, agriculture, housing, etc., that absolutely must be operational on time. Full article

Neutron–antineutron oscillation (nnbar-osc) is a baryon number-violating process and a sensitive probe for physics beyond the standard model. Ultra-cold neutrons (UCNs) are attractive for nnbar-osc searches because of their long storage time, but earlier analyses indicated that phase shifts on wall reflection differ for neutrons and antineutrons, leading to severe decoherence and a loss of sensitivity. Herein, we revisit this problem by numerically solving the time-dependent Schrödinger equation for the two-component n/nbar wave function, explicitly including wall interactions. We show that decoherence can be strongly suppressed by selecting a wall material whose neutron and antineutron optical potentials are nearly equal. Using coherent scattering length data and estimates for antineutrons, we identify a Ni–Al alloy composition that matches the potentials within a few percent while providing a high absolute value, enabling long UCN storage. With such a bottle and an improved UCN source, the sensitivity could reach an oscillation period ${\tau }_{nnbar}$ of the order 10¹⁰ s, covering most of the range predicted with certain grand unified models. This approach revives the feasibility of high-sensitivity nnbar-osc searches using stored UCNs and offers a clear path to probe baryon number violation far beyond existing limits. Full article

Dams play a vital role in securing water and electricity supplies for households and industry, and they contribute significantly to flood protection. Regular monitoring of dam deformations holds fundamental socio-economic and ecological importance. Traditionally, this has relied on time-consuming in situ techniques that offer either high spatial or temporal resolution. Persistent Scatterer Interferometry (PSI) addresses these limitations, enabling high-resolution monitoring in both domains. Sensors such as TerraSAR-X (TSX) and Sentinel-1 (S-1) have proven effective for deformation analysis with millimeter accuracy. Combining TSX and S-1 datasets enhances monitoring capabilities by leveraging the high spatial resolution of TSX with the broad coverage of S-1. This improves monitoring by increasing PS point density, reducing revisit intervals, and facilitating the detection of environmental deformation drivers. This study aims to investigate two objectives: first, we evaluate the benefits of a spatially and temporally densified PS time series derived from TSX and S-1 data for detecting radial deformations in individual dam segments. To support this, we developed the TSX2StaMPS toolbox, integrated into the updated snap2stamps workflow for generating single-master interferogram stacks using TSX data. Second, we identify deformation drivers using water level and temperature as exogenous variables. The five-year study period (2017–2022) was conducted on a gravity dam in North Rhine-Westphalia, Germany, which was divided into logically connected segments. The results were compared to in situ data obtained from pendulum measurements. Linear models demonstrated a fair agreement between the combined time series and the pendulum data ($R^2$ = 0.5; MAE = 2.3 mm). Temperature was identified as the primary long-term driver of periodic deformations of the gravity dam. Following the filling of the reservoir, the variance in the PS data increased from 0.9 mm to 3.9 mm in RMSE, suggesting that water level changes are more responsible for short-term variations in the SAR signal. Upon full impoundment, the mean deformation amplitude decreased by approximately 1.7 mm toward the downstream side of the dam, which was attributed to the higher water pressure. The last five meters of water level rise resulted in higher feature importance due to interaction effects with temperature. The study concludes that integrating multiple PS datasets for dam monitoring is beneficial particularly for dams where few PS points can be identified using one sensor or where pendulum systems are not installed. Identifying the drivers of deformation is feasible and can be incorporated into existing monitoring frameworks. Full article

The article is aimed at building on the existing studies devoted to the last stage of the assimilation policy directed at the Muslim population in Communist Bulgaria during the second half of the 1980s. The 40th anniversary of the forced change of the given Turkish–Arabic and Persian names of this population is an occasion to revisit this dark period of the recent past. This study focuses on the short- and long-term consequences of the political measures, which became known as the ‘Revival process’ (1984/1985–1989). For the first time, the author presents new written sources, including analytical and field reports commissioned by the Central Committee of the Bulgarian Communist Party and prepared by Bulgarian scholars during the second half of the 1980s, as well as later collected biographical data related to Muslims affected by the events, derived through an (auto)ethnographic method of research among Turks, Crimean Tatars and Muslim Roma. Full article

Dietary choices and patterns have enormous consequences along the lines of individual, community, and planetary health. Excess meat consumption has been linked to chronic disease risk, and at large scales, the underlying industries maintain a massive environmental footprint. For these reasons, public and planetary health experts are unified in emphasizing a whole or minimally processed plant-based diet. In response, the purveyors of ultra-processed foods have added “meat alternatives” to their ultra-processed commercial portfolios; multinational corporations have been joined by “start-ups” with new ultra-processed meat analogues. Here, in our Viewpoint, we revisit the 1990s food industry rhetoric and product innovation, a time in which multinational corporations pushed a great “low-fat transition.” We focus on the McLean Deluxe burger, a carrageenan-rich product introduced by the McDonald’s Corporation in 1991. Propelled by a marketing and media-driven fear of dietary fats, the lower-fat burger was presented with great fanfare. We reflect this history off the current “great protein transition,” a period once again rich in rhetoric, with similar displays of industry detachment from concerns about the health consequences of innovation. We scrutinize the safety of carrageenan and argue that the McLean burger should serve as a cautionary tale for planetary health and 21st century food innovation. Full article

Mining activities can trigger geological disasters, including slope instability and surface subsidence, posing a serious threat to the surrounding environment and miners’ safety. Consequently, the development of reasonable, effective, and rapid deformation monitoring methods in mining areas is essential. Traditional synthetic aperture radar(SAR) satellites are often limited by their revisiting period and image resolution, leading to unwrapping errors and decorrelation issues in the central mining area, which pose challenges in deformation monitoring in mining areas. In this study, persistent scatterer interferometric synthetic aperture radar (PS-InSAR) technology is used to monitor and analyze surface deformation of the Jinchuan mining area in Jinchang City, based on SAR images from the small satellites “Fucheng-1” and “Shenqi”, launched by the Tianyi Research Institute in Hunan Province, China. Notably, the dual-star constellation offers high-resolution SAR data with a spatial resolution of up to 3 m and a minimum revisit period of 4 days. We also assessed the stability of the dual-star interferometric capability, imaging quality, and time-series monitoring capability of the “Fucheng-1” and “Shenqi” satellites and performed a comparison with the time-series results from Sentinel-1A. The results show that the phase difference (SPD) and phase standard deviation (PSD) mean values for the “Fucheng-1” and “Shenqi” interferograms show improvements of 21.47% and 35.47%, respectively, compared to Sentinel-1A interferograms. Additionally, the processing results of the dual-satellite constellation exhibit spatial distribution characteristics highly consistent with those of Sentinel-1A, while demonstrating relatively better detail representation capabilities at certain measurement points. In the context of rapid deformation monitoring in mining areas, they show a higher revisit frequency and spatial resolution, demonstrating high practical value. Full article

Ground-based synthetic aperture radar (GBSAR) has been widely used in the fields of early warning of geologic hazards and deformation monitoring of engineering structures due to its characteristics of high spatial resolution, zero spatial baseline, and short revisit period. However, in the continuous monitoring process of GBSAR, due to the sudden failure of radar equipment, such as power failure, or the influence of alternating work between multiple regions, it often leads to discontinuous data collection, and this problem caused by missing data is collectively called “inspection mode”. The problem of missing data in the inspection mode not only destroys the spatial and temporal continuity of the data but also affects the accuracy of the subsequent deformation analysis. In order to solve this problem, in this paper, we propose a data reconstruction method that combines Sage–Husa Kalman adaptive filtering and the Rauch–Tung–Striebel (RTS) smoothing algorithm. The method is based on the principle of Kalman filtering and solves the problem of “model mismatch” caused by the fixed noise statistics of traditional Kalman filtering by dynamically adjusting the noise covariance to adapt to the non-stationary characteristics of the observed data. Subsequently, the Rauch–Tung–Striebel (RTS) smoothing algorithm is used to process the preliminary filtering results to eliminate the cumulative error during the period of missing data and recover the complete and smooth deformation time series. The experimental and simulation results show that this method successfully restores the spatial and temporal continuity of the inspection data, thus improving the overall accuracy and stability of deformation monitoring. Full article

This study utilizes the unique capabilities of Sentinel-1 C-band synthetic aperture radar (SAR) data to map post-fire burned areas and monitor vegetation recovery in a heath-dominated Queensland National Park. Sentinel-1 SAR data were used due to their cloud-penetrating capability and frequent revisit times. Using Google Earth Engine (GEE), a bitemporal ratio analysis was applied to SAR data from post-fire periods between 2021 and 2023. SAR backscatter changes over time captured fire impacts and subsequent vegetation regrowth. This differentiation was further enhanced with k-means clustering. Validation was supported by Sentinel-2 dNBR and official fire history records. The dNBR provided a quantitative assessment of burn severity and was used alongside the fire history data to evaluate the accuracy of the burned area classification. While Sentinel-2 false-colour composite (FCC) imagery was generated for visualisation and interpretation purposes, the primary validation relied on dNBR and QPWS fire history records. The results highlighted significant vegetation regrowth, with some areas returning to near pre-fire biomass levels by March 2023. This approach demonstrates the sensitivity of Sentinel-1 SAR, especially in VV polarization, for detecting subtle changes in vegetation, providing a cost-effective method for post-fire ecosystem monitoring and informing ecological management strategies amid increasing wildfire events. Full article

In this paper, the Balassa–Samuelson–Tariffi effect is revisited. This research first aims to explain that the behaviour of the real exchange rate shows structural breaks in the short term. A partial equilibrium model “á la Rogoff” is formally formulated where there are relative prices of non-tradable goods in terms of tradable goods in the supply side. Secondly, a general equilibrium model is built after a utility function is added to the partial equilibrium model. It is presented as a mathematical mechanism that shows a stationary state in the real exchange rate considering not only non-tradable goods but also tradable goods both in the domestic market and the foreign market. It is explained that any change in a currency’s price in terms of another currency in real terms is transitory in the long run, thereby disappearing after a certain period of time. In the general equilibrium model, any price’s change in non-tradable goods will be compensated by either a price’s change in tradable goods or changes in the nominal exchange rate. Therefore, this study’s main contribution is to show theoretically that the real exchange rate is constant over time in the long run. Full article

Fast radio bursts (FRBs) are luminous radio transients with millisecond duration. For some active repeaters, such as FRBs 20121102A and 20201124A, more than a thousand bursts have been detected by the Five-hundred-meter Aperture Spherical radio Telescope (FAST). The waiting time (WT) distributions of both repeaters, defined as the time intervals between adjacent (detected) bursts, exhibit a bimodal structure well-fitted by two log-normal functions. Notably, the time scales of the long-duration WT peaks for both repeaters show a decreasing trend over time. These similar burst features suggest that there may be a common physical mechanism for FRBs 20121102A and 20201124A. In this paper, we revisit the neutron star (NS)–white dwarf (WD) binary model with an eccentric orbit to account for the observed changes in the long-duration WT peaks. According to our model, the shortening of the WT peaks corresponds to the orbital period decay of the NS-WD binary. We consider two mass transfer modes, namely, stable and unstable mass transfer, to examine how the orbital period evolves. Our findings reveal distinct evolutionary pathways for the two repeaters: for FRB 20121102A, the NS-WD binary likely undergoes a combination of common envelope (CE) ejection and Roche lobe overflow, whereas for FRB 20201124A the system may experience multiple CE ejections. These findings warrant further validation through follow-up observations. Full article

Variations in stratospheric atmospheric circulation significantly impact tropospheric weather and climate. Understanding these variations not only aids in better prediction of tropospheric weather and climate but also provides guidance for the development and flight trajectories of stratospheric aircraft. Our understanding of the stratosphere has made remarkable progress over the past 100 years. However, we still lack a comprehensive perspective on large-scale patterns in stratospheric circulation, as the stratosphere is a typical complex system. To address this gap, we employed the eigen microstate approach (EMA) to revisit the characteristics of zonal wind from 70–10 hPa from 1980 to 2022, based on ERA5 reanalysis data. Our analysis focused on the three leading modes, corresponding to variations in the strength of the quasi-biennial oscillation (QBO) and the stratospheric atmospheric circulations in the Arctic and Antarctic, respectively. After filtering out high-frequency components from the temporal evolutions of these modes, a significant 11-year cycle was observed in the Antarctic stratospheric atmospheric circulation mode, potentially linked to the 11-year solar cycle. In contrast, the Arctic stratospheric atmospheric circulation mode showed a 5–6-year cycle without evidence of an 11-year periodicity. This difference is likely due to the timing of polar vortex breakdowns: the Antarctic polar vortex breaks up later, experiencing its greatest variability in late spring and early summer, making it more susceptible to solar radiation effects, unlike the Arctic polar vortex, which peaks in winter and early spring. The fourth mode exhibits characteristics of a Southern Hemisphere dipole and shows a significant correlation with the Antarctic stratospheric atmospheric circulation mode, leading it by about two months. We designed a linear prediction model that successfully demonstrated its predictive capability for the Antarctic polar vortex. Full article

Oases are part of the natural wealth and heritage of Morocco and contribute to the social, economic, and touristic environment. Morocco has lost more than 2/3 of its oases during the past century due to water scarcity, succession of drought periods, climate change and over-exploitation of groundwater resources. Palm trees are strongly dependent on irrigation and availability of surface water as soon as the water table depth falls below the root zone of 9 m. Improving management and monitoring of oasis ecosystems is strongly encouraged by UNESCO Biosphere Reserve and RAMSAR guidelines. The Boudenib and Tafilalet oases are among the biggest palm groves located in the south-eastern part of Morocco. These oases belong to catchments of the rivers Guir and Ziz, respectively. This paper uses remotely sensed data from PROBA-V for monitoring vegetation in oases, and linking vegetation characteristics to water availability, water management and quality and quantity of date crops. The Normalized Differential Vegetation Index (NDVI) derived from optical images provides a good estimation of changes in vegetation cover over time. Images of various spatial resolutions (100 m, 300 m and 1 km) obtained with the frequently revisiting Belgian satellite PROBA-V and available since 2014, can be successfully used for deriving time series of vegetation dynamics. TREX—Tool for Raster data Exploration—is a Python-GDAL processing tool of PROBA-V NDVI images for analyzing vegetation dynamics, developed at the Vrije Universiteit Brussel and available online. TREX has various applications, but the main functionality is to provide an automatic processing of PROBA-V satellite images into time series of NDVI and LAI, used in vegetation monitoring of user-defined points of interest. This study presents the results of application of TREX in the arid ecosystems of the Boudenib oasis for the period 2014–2018. The resulting NDVI and LAI time series are also compared to time series of groundwater depth and date crops quantity and quality. Low LAI is observed when water depth is low, and the palm trees lose their greenery. Low LAI is also correlated to low quantity and quality of dates in October 2015 and October 2017. PROBA-V images can therefore be used for monitoring the health of palm trees in oasis environments. However, considering the fact that the PROBA-V satellite mission has ended, this approach could instead be applied to Sentinel-3 data using the same analysis. These results have important implications for water management in the area and can help decision-makers to make better decisions about prevention of water scarcity in the region. Full article

The present study is based on a follow-up of a survey carried out in 2000, consisting in the revisitation of ten sites, with the scope of assessing changes in the composition and richness of epiphytic macrolichens within Cluj-Napoca city over the past 24 years. Within this period most of the polluting factories from the city outskirts were closed but in turn, the number of registered cars increased almost six-fold. An increasing compositional homogenization by contribution of generalist, stress-tolerant species was detected over time while total lichen taxa richness declined, which is mostly imputable to the synergic effects of intense car traffic and warmer/drier summers. Most sites displayed a compositional change along a weak, mixed gradient of eutrophication and xerophitization. Only two sites (located on the windy, Someș valley bottom) experienced a compositional change from higher to lower trophicity levels. Other two sites (positioned on more sheltered hillsides) displayed unfavourable dynamics in terms of lost species. Unexpectedly, the number of epiphytic lichen taxa at site level has, on average, increased over time, but the main contributors were poleotolerant species. The warming trend, due to climate change and local heat sources, is expected to worsen the negative effects of air-borne pollutants on the composition of the epiphytic lichen species pool within the Cluj-Napoca urban area. Full article

Traditional methods for estimating tea yield mainly rely on manual sampling surveys and empirical estimation, which are labor-intensive and time-consuming. Accurately estimating fresh tea production in different seasons has become a challenging task. It is possible to estimate the seasonal yield of tea at the field scale by using the spatial resolution of 10 m, 5-day revisit period and rich spectral information of Sentinel-2 imagery. This study integrated Sentinel-2 images and uncrewed aerial vehicle (UAV) RGB imagery to develop six regression models at the field scale, which were employed for the estimation of seasonal and annual fresh tea yields of the Yunlong Tea Cooperatives in Yixiang Town, Pu’er City, China. Firstly, we gathered fresh tea production data from 133 farmers in the cooperative over the past five years and obtained UAV RGB and Sentinel-2 imagery. Secondly, 23 spectral features were extracted from Sentinel-2 images. Based on the UAV images, the parcel of each farmer was positioned and three topographic features of slope, aspect, and elevation were extracted. Subsequently, these 26 features were screened using the random forest algorithm and Pearson correlation analysis. Thirdly, we applied six different regression algorithms to establish fresh tea yield models for each season and evaluated their estimation accuracy. The results showed that random forest regression models were the optimal choice for estimating spring and summer yields, with the spring model achieving an R² value of 0.45, an RMSE of 40.38 kg/acre, and an rRMSE of 40.79%. Similarly, the summer model achieved an R² value of 0.5, an RMSE of 78.46 kg/acre, and an rRMSE of 39.81%. For autumn and annual yield estimation, voting regression models demonstrated superior performance, with the autumn model achieving an R² value of 0.42, an RMSE of 70.6 kg/acre, and an rRMSE of 39.77%, and the annual model attained an R² value of 0.47, an RMSE of 168.7 kg/acre, and an rRMSE of 34.62%. This study provides a promising new method for estimating fresh tea yield in different seasons at the field scale. Full article