Small Scale Research Articles

Service to demands and corruption tolerance: brazilian voters' perception of “rouba, mas faz” policy

Purpose: The research aimed to verify the influence of meeting public demands on the perception of tolerance of Brazilian voters towards the “rouba, mas faz” policy. Although a social unison of rejection of corruption in politics is perceived, there is a possibility that voters relax this disapproval in the face of the results that managers offer to communities. Methodology: Study of quantitative approach, as for the procedures, a survey was used, with a questionnaire and study of scenarios, of tolerance to “rouba, mas faz”, as a research instrument. To analyze the data, descriptive statistics and presentation in percentages were used for the answers to assertions and scenarios. Results: The results indicate that Brazilians demand honest politicians, although for almost 25% of the population every politician is corrupt, without distinction; for 80% of respondents the main cause of problems in Brazilian public management is political corruption; approximately 70% of voters do not use transparency portals to decide their vote, although 80% claim to research the candidates' history before making their decision. Contributions of the Study: Aspects related to the median voter theory were perceived, since, although Brazilian voters demonstrate intolerance to corruption, the profile with the average characteristics of the population tends to vote for that candidate who promises to meet their needs. In addition, in general terms, 7% of the sample would re-elect a very corrupt politician, as long as he is very productive, while 24% would tolerate corruption, as long as it occurs on a small scale and is accompanied by works and benefits to society, implying that there is, in general terms, to a certain degree, the influence of meeting public demands on voters' tolerance of the “rouba, mas faz” policy in Brazil.

Adoption potential of black soldier fly (Hermetia illucens (L.), Diptera: Stratiomyidae) larvae composting technology among smallholder farmers in Greater Ahafo-Ano, Ashanti region of Ghana

As the world’s population increases, the growing demand for food intensifies the generation of agricultural waste, leading to several environmental issues. Intensive research indicates black soldier fly (BSF) larvae Hermetia illucens (Linnaeus, 1758) as efficient converters of organic waste into nutrient-rich biomass suitable for animal feed. Using a structured questionnaire and volunteer farmers (N = 595), we investigated the potential for adoption of BSF larvae composting technology for sustainable agricultural waste management in Greater Ahafo-Ano. Almost all surveyed farmers declared they generated a significant amount of biowaste on their farms and were willing to learn how to use the BSF-based technology to transform it into value-added products. The waste generated was mainly disposed of in pits at Ahafo-Ano South-East (56.2%), by composting at Ahafo-Ano South-West (34.9%) and by sale at Ahafo-Ano North (34.4%). Across the three districts, awareness of the BSF was very low – 14.5% in Ahafo-Ano South-East, 14.1% in Ahafo-Ano South-West and 0.5% in Ahafo-Ano North. However, high acceptance of the technology was recorded. It was found that about 8% of farmers surveyed in Ahafo-Ano South-East had already tried BSF farming on a small scale. Indicating this district as a good entry point to introduce the technology into Greater Ahafo-Ano.

High levels of species' extirpation in an urban environment-A case study from Berlin, Germany, covering 1700-2023.

Species loss is highly scale-dependent, following the species-area relationship. We analysed spatio-temporal patterns of species' extirpation on a multitaxonomic level using Berlin, the capital city of Germany. Berlin is one of the largest cities in Europe and has experienced a strong urbanisation trend since the late nineteenth century. We expected species' extirpation to be exceptionally high due to the long history of urbanisation. Analysing 37 regional Red Lists of Threatened Plants, Animals and Fungi of Berlin (covering 9498 species), we found that 16% of species were extirpated, a rate 5.9 times higher than at the German scale and 47.1 times higher than at the European scale. Species' extirpation in Berlin is comparable to that of another German city with a similarly broad taxonomic coverage, but much higher than in regional areas with less human impact. The documentation of species' extirpation started in the eighteenth century and is well documented for the nineteenth and twentieth centuries. We found an average annual extirpation of 3.6 species in the nineteenth century, 9.6 species in the twentieth century and the same number of extirpated species as in the nineteenth century were documented in the twenty-first century, despite the much shorter time period. Our results showed that species' extirpation is higher at small than on large spatial scales, and might be negatively influenced by urbanisation, with different effects on different taxonomic groups and habitats. Over time, we found that species' extirpation is highest during periods of high human alterations and is negatively affected by the number of people living in the city. But, there is still a lack of data to decouple the size of the area and the human impact of urbanisation. However, cities might be suitable systems for studying species' extirpation processes due to their small scale and human impact.

Late syn‐rift to early post‐rift basin fill dynamics of a mixed siliciclastic‐carbonate succession banked to a basement high, Hornsund, southwestern Spitsbergen, Arctic Norway

AbstractThe transition from syn‐rift to post‐rift sedimentation in rift basins is difficult to characterize in terms of stratigraphic architecture and dominating control on sedimentation, due to decreasing tectonic activity interplaying with regional subsidence, eustatic sea level changes, and differential compaction of underlying syn‐rift sediments. Our case study of the Late Palaeozoic Inner Hornsund Fault Zone targets late syn‐rift strata recorded in the (?Pennsylvanian – ?lower Permian) Treskelodden Formation in Hornsund, southern Spitsbergen, representing a mixed siliciclastic‐carbonate succession, with siliciclastics primarily sourced from the adjacent Sørkapp‐Hornsund High. We document local scale (<10 km) facies variability, sequence stratigraphy, and evolution of a succession deposited along a flank of the structural high during the late syn‐rift stage. We observe that during the transition towards rift termination (glacio‐)eustatic sea level changes and overall regional flooding became a more prominent forcing factor controlling sedimentation. Our dataset includes sedimentary logs, microfacies analysis, and high‐resolution digital outcrop models. We identify four progressively backstepping stratigraphic sequences, reflecting an evolution from (1) terrestrial siliciclastics through (2–3) nearshore mixed siliciclastic–carbonates, to (4) carbonate ramp deposits. On the small scale (<5 m) the internal sediment cyclicity of the succession was formed by autogenic processes, particularly the changing rate of sediment input from the southwestern source area (the uplifted Sørkapp‐Hornsund basement high). On the larger scale (10s of m), the importance of glacio‐eustatic sea‐level changes, driven by waxing and waning of ice caps in the southern hemisphere (Gondwana), increased as the rift‐related tectonics decreased. The interdisciplinary methods used in this study provide new knowledge of the Middle Pennsylvanian to Permian depositional evolution in southern Spitsbergen, besides a novel framework for comparison to adjacent basins in the region and similar basins elsewhere.

Numerical simulation and thermodynamic test analysis of plate heat exchanger based on topology optimization

Efficient heat transfer in PHEs relies on optimizing flow distribution to minimize thermal dead zones. Existing studies have predominantly focused on single-phase fluids as working media and employed density-based methods for structural optimization of microchannel heat exchangers at small scales. In this study, the Brinkman term from the porous media flow model is introduced in an innovative manner, along with the utilization of a material density interpolation model, which builds upon the density-based approach. A novel two-phase fluid topology optimization method is proposed, specifically tailored for large-scale PHE operating conditions, resulting in the successful design of a new PHE topology. To compare the performance of the two heat exchangers, finite element simulation, visualization experiments, and thermodynamic performance testing are conducted. The simulation results reveal that the heat transfer capacity of the topological PHE is 810 W with pressure drops of 18.8 kPa, while the dimple PHE exhibits heat transfer capacity of 652 W with pressure drops of 25.9 kPa. Compared to the dimple PHE, the topological PHE demonstrates 24.2 % improvement in heat transfer performance and 27.8 % reduction in pressure drop. The dimensionless comprehensive heat transfer coefficient (j/f) indicates that the overall performance of the topological PHE significantly surpasses that of the traditional PHE. Furthermore, the visualization experiment results demonstrate that the complex texture structure of the topological PHE effectively induces fluid motion, compelling the fluid to flow along the texture direction. This significantly mitigates the issue of uneven flow within the PHE, thus enhancing heat transfer efficiency. Specifically, the topological PHE exhibits inlet–outlet temperature difference of 10.3 °C and pressure drops of 11.2 kPa, while the dimple PHE shows inlet–outlet temperature difference of 6 °C and pressure drops of 12.9 kPa. The findings of this study provide guidance for future research endeavors aimed at evaluating potential solutions to advance heat transfer in PHEs and facilitate the implementation of thermal management strategies.

Kirigami sheets in fluid flow

Kirigami patterned materials have found several applications in recent years due to their ability to assume complicated shapes and exhibit emergent physical properties when exposed to external forces. Consisting of an array of cuts in a thin material, fabrication of these patterns can be quite simple. Here we show that when they are placed in fluid flow, kirigami cut sheets with various patterns produce a variety of flow patterns in the wake. Through several sets of experiments, we show that kirigami sheets placed in flow can undergo static or dynamic flow-induced instabilities as a result of which they can buckle or undergo limit cycle oscillations, or they can remain stable while undergoing very large elongations. These structural responses produce several different types of fluid patterns in the wake. We show that vortices both at small scales (scales comparable with the size of the individual kirigami cuts) and large scale (scales comparable with the size of the sheet) are formed in the wake of kirigami sheets. We also show that jets of different sizes can be formed and directed passively using kirigami sheets. These results show the potential of kirigami sheets for passive flow control.

Phylogenetic indices and temporal and spatial scales shape the neighborhood effect on seedling survival in a mid-mountain moist evergreen broad-leaved forest, Gaoligong Mountains, Southwestern China.

Density dependence and habitat filtering have been proposed to aid in understanding community assembly and species coexistence. Phylogenetic relatedness between neighbors was used as a proxy for assessing the degree of ecological similarity among species. There are different conclusions regarding the neighborhood effect in previous studies with different phylogenetic indices or at different spatiotemporal scales. However, the effects of density dependence, neighbor phylogenetic relatedness, and habitat filtering on seedling survival with different phylogenetic indices or at different temporal and spatial scales are poorly understood. We monitored 916 seedlings representing 56 woody plant species within a 4-ha forest dynamics plot for 4 years (from 2020 to 2023) in a subtropical mid-mountain moist evergreen broad-leaved forest in the Gaoligong Mountains, Southwestern China. Using generalized linear mixed models, we tested whether and how four phylogenetic indices: total phylogenetic distance (TOTPd), average phylogenetic distance (AVEPd), relative average phylogenetic distance (APd'), and relative nearest taxon phylogenetic distance (NTPd'), three temporals (1, 2, and 3 years), and spatial scales (1, 2, and 4 ha) affect the effect of density dependence, phylogenetic density dependence, and habitat filtering on seedling survival. We found evidence of the effect of phylogenetic density dependence in the 4-ha forest dynamics plot. The effects of density dependence, phylogenetic density dependence, and habitat filtering on seedling survival were influenced by phylogenetic indices and temporal and spatial scales. The effects of phylogenetic density dependence and habitat filtering on seedling survival were more conspicuous only at 1-year intervals, compared with those at 2- and 3-year intervals. We did not detect any effects of neighborhood or habitat factors on seedling survival at small scales (1 and 2 ha), although these effects were more evident at the largest spatial scale (4 ha). These findings highlight that the effects of local neighborhoods and habitats on seedling survival are affected by phylogenetic indices as well as temporal and spatial scales. Our study suggested that phylogenetic index APd', shortest time scale (1 year), and largest spatial scales (4 ha) were suitable for neighborhood studies in a mid-mountain moist evergreen broad-leaved forest in Gaoligong Mountains. Phylogenetic indices and spatiotemporal scales have important impacts on the results of the neighborhood studies.

Primordial magnetic fields: consistent initial conditions and impact on high-z structures

Primordial magnetic fields (PMFs) can enhance matter power spectrum on small scales (≲ Mpc) and still agree with bounds from cosmic microwave background (CMB) and Faraday rotation measurements. As modes on scales smaller than Mpc have already become non-linear today, exploring PMFs' impact on small-scale structures requires dedicated cosmological simulations. Here, for the first time, we perform a suite of hydrodynamical simulations that take into account the different impacts of PMFs on baryons and dark matter. Specifically, in the initial conditions we displace particles according to the Lorentz force from PMFs. We also highlight the large theoretical uncertainty in the peak enhancement of the matter power spectrum due to PMFs, which was not considered in previous studies. We present halo mass functions and show that they can be accurately reproduced using Sheth-Tormen formalism. Moreover, we show that PMFs can generate galaxies with baryon fraction several times larger than the cosmic average at high redshifts. This is simply a consequence of the fact that PMFs enhance baryon perturbations, causing them to be larger than dark matter perturbations. We argue that this scenario could be tested soon by obtaining accurate estimates of the baryon fraction in high redshift galaxies.

Geometry, Dissipation, Cooling, and the Dynamical Evolution of Wind-blown Bubbles

Bubbles driven by energy and mass injection from small scales are ubiquitous in astrophysical fluid systems and essential to feedback across multiple scales. In particular, O stars in young clusters produce high-velocity winds that create hot bubbles in the surrounding gas. We demonstrate that the dynamical evolution of these bubbles is critically dependent upon the geometry of their interfaces with their surroundings and the nature of heat transport across these interfaces. These factors together determine the amount of energy that can be lost from the interior through cooling at the interface, which in turn determines the ability of the bubble to do work on its surroundings. We further demonstrate that the scales relevant to physical dissipation across this interface are extremely difficult to resolve in global numerical simulations of bubbles for parameter values of interest. This means the dissipation driving evolution of these bubbles in numerical simulations is often of a numerical nature. We describe the physical and numerical principles that determine the level of dissipation in these simulations; we use this, along with a fractal model for the geometry of the interfaces, to explain differences in convergence behavior between hydrodynamical and magnetohydrodynamical simulations presented here. We additionally derive an expression for momentum as a function of bubble radius expected when the relevant dissipative scales are resolved and show that it still results in efficiently cooled solutions, as postulated in previous work.

Kinetic recoupling of dark matter

We study the possibility that dark matter re-enters kinetic equilibrium with a radiation bath after kinetic decoupling, a scenario we dub kinetic recoupling. This naturally occurs, for instance, with certain types of resonantly-enhanced interactions, or as the result of a phase transition. While late kinetic decoupling damps structure on small scales below a cutoff, kinetic recoupling produces more complex changes in the power spectrum that depend on the nature and extent of the recoupling period. We explore the features that kinetic recoupling imprints upon the matter power spectrum, and discuss how such features can be traced to dark matter microphysics with future observations.

Feature boosting with efficient attention for scene parsing

The complexity of scene parsing grows with the number of object and scene classes, which is higher in unrestricted open scenes. The biggest challenge is to model the spatial relation between scene elements while succeeding in identifying objects at smaller scales. This paper presents a novel feature-boosting network that gathers spatial context from multiple levels of feature extraction and computes the attention weights for each level of representation to generate the final class labels. A novel ‘channel attention module’ is designed to compute the attention weights, ensuring that features from the relevant extraction stages are boosted while the others are attenuated. The model also learns spatial context information at low resolution to preserve the abstract spatial relationships among scene elements and reduce computational cost. Spatial attention is subsequently concatenated into a final feature set before applying feature boosting. Low-resolution spatial attention features are trained using an auxiliary task that help to learn a coarse global scene structure. The proposed model outperforms all state-of-the-art models on both the ADE20K and the Cityscapes datasets.

Surface Brightness Fluctuations in Two SPT Clusters: A Pilot Study

Studies of surface brightness fluctuations in the intracluster medium present an indirect probe of turbulent properties such as the turbulent velocities, injection scales, and the slope of the power spectrum of fluctuations toward smaller scales. With the advancement of Sunyaev–Zel’dovich (SZ) studies and surveys relative to X-ray observations, we seek to investigate surface brightness fluctuations in a sample of South Pole Telescope (SPT)-SZ clusters which also have archival XMM-Newton data. Here we present a pilot study of two typical clusters in that sample: SPT-CLJ0232-4421 and SPT-CLJ0638-5358. We infer injection scales larger than 500 kpc in both clusters and Mach numbers ≈ 0.5 in SPT-CLJ0232-4421 and Mach numbers ≈ 0.6–1.6 in SPT-CLJ0638-5358, which has a known shock. We find hydrostatic bias values for M 500 less than 0.2 for SPT-CLJ0232-4421 and less than 0.1 for SPT-CLJ0638-5358. These results show the importance to assess quantitative values via a detailed multiwavelength approach and suggest that the drivers of turbulence may occur at quite large scales.

Refined and dynamic susceptibility assessment of landslides using InSAR and machine learning models

Landslide susceptibility assessment is crucial in predicting landslide occurrence and potential risks. However, traditional methods usually emphasize on larger regions of landsliding and rely on relatively static environmental conditions, which exposes the hysteresis of landslide susceptibility assessment in refined-scale and temporal dynamic changes. This study presents an improved landslide susceptibility assessment approach by integrating machine learning models based on random forest (RF), logical regression (LR), and gradient boosting decision tree (GBDT) with interferometric synthetic aperture radar (InSAR) technology and comparing them to their respective original models. The results demonstrated that the combined approach improves prediction accuracy and reduces the false negative and false positive errors. The LR-InSAR model showed the best performance in dynamic landslide susceptibility assessment at both regional and smaller scale, particularly when identifying areas of high and very high susceptibility. Modeling results were verified using data from field investigations including unmanned aerial vehicle (UAV) flights. This study is of great significance to accurately assess dynamic landslide susceptibility and to help reduce and prevent landslide risk.

Enhancing bivariate spatial association analysis of network-constrained geographical flows: an incremental scale-based method

Measuring bivariate spatial association plays a key role in understanding the spatial relationships between two types of geographical flow (hereafter referred to as “flow”). However, existing studies usually use multiple scales to analyze bivariate associations of flows, leading to the results at larger scales can be strongly affected by the results at smaller scales. Moreover, the planar space assumption of most existing studies is unsuitable for network-constrained flows. To solve these problems, a network incremental flow cross K-function (NIFK) is developed in this study by extending the cross K-function for points into a flow context. Specifically, two versions of NIFK were developed in this study: the global version to check whether bivariate associations exist in the whole study area and the local version to identify specific locations where associations occur. Experiments on three simulated datasets demonstrate the advantages of the proposed method over an available alternative method. A case study conducted using Xiamen taxi and ride-hailing service datasets demonstrates the usefulness of the proposed method. The detected bivariate spatial association provides deep insights for understanding the competition between taxi services and ride-hailing services.

Efficient reduction of power losses by allocating various DG types using the ZOA algorithm

The continuous challenge of ensuring energy supply is a significant concern. Traditionally, utilities have addressed increasing load demands by building new central power plants or expanding existing ones. However, these methods are time-consuming and costly, providing only short-term solutions. Additionally, power plants are often far from load centers, resulting in higher power losses during long-distance transmission. The integration of distributed generation (DG), characterized by smaller scale and lower capital costs, with nearby consumers can effectively address these challenges. Due to the significant influence of DG penetration and their specific locations on the distribution system's performance, this study offers a novel Zebra Optimization Algorithm (ZOA). The suggested ZOA is used to optimize the capacity and position of various DG units connected to a radial distribution system to reduce power losses and study the stability of the system after DG allocation using the Voltage Stability Index (VSI). The evaluation is conducted using the IEEE 33-bus test system, considering various scenarios including single and multiple DGs of different types. The results demonstrate that in the best scenario, the ZOA can reduce losses by up to 94.25 % and improve the VSI from 0.69643 to 0.9605. These findings highlight the superior performance of the ZOA over other techniques in optimizing DG placement and sizing for power system performance.

Filament eruption by multiple reconnections

Context. Filament eruption is a common phenomenon in solar activity, but the triggering mechanism is not well understood. Aims. We focus our study on a filament eruption located in a complex nest of three active regions close to a coronal hole. Methods. The filament eruption is observed at multiple wavelengths: by the Global Oscillation Network Group (GONG), the Solar Terrestrial Relations Observatory (STEREO), the Solar Upper Transition Region Imager (SUTRI), and the Atmospheric Imaging Assembly (AIA) and Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamic Observatory (SDO). Thanks to high-temporal-resolution observations, we were able to analyze the evolution of the fine structure of the filament in detail. The filament changes direction during the eruption, which is followed by a halo coronal mass ejection detected by the Large Angle Spectrometric Coronagraph (LASCO) on board the Solar and Heliospheric Observatory (SOHO). A Type III radio burst was also registered at the time of the eruption. To investigate the process of the eruption, we analyzed the magnetic topology of the filament region adopting a nonlinear force-free-field (NLFFF) extrapolation method and the polytropic global magnetohydrodynamic (MHD) modeling. We modeled the filament by embedding a twisted flux rope with the regularized Biot-Savart Laws (RBSL) method in the ambient magnetic field. Results. The extrapolation results show that magnetic reconnection occurs in a fan-spine configuration resulting in a circular flare ribbon. The global modeling of the corona demonstrates that there was an interaction between the filament and open field lines, causing a deflection of the filament in the direction of the observed CME eruption and dimming area. Conclusions. The modeling supports the following scenario: magnetic reconnection not only occurs with the filament itself (the flux rope) but also with the background magnetic field lines and open field lines of the coronal hole located to the east of the flux rope. This multiwavelength analysis indicates that the filament undergoes multiple magnetic reconnections on small and large scales with a drifting of the flux rope.

The spatial distribution of heat related hospitalizations and classification of the most dangerous heat events in California at a small-scale level

Many studies have explored the impact of extreme heat on health, but few have investigated localized heat-health outcomes across a wide area. We examined fine-scale variability in vulnerable areas, considering population distribution, local weather, and landscape characteristics. Using 36 different heat event definitions, we identified the most dangerous types of heat events based on minimum, maximum, and diurnal temperatures with varying thresholds and durations. Focusing on California's diverse climate, elevation, and population distribution, we analyzed hospital admissions for various causes of admission (2004–2013). Our matching approach identified vulnerable zip codes, even with small populations, on absolute and relative scales. Bayesian Hierarchical models leveraged spatial correlation. We ranked the 36 heat event types by attributable hospital admissions per zip code and provided code, simulated data, and an interactive web app for reproducibility. Our findings showed high variation in heat-related hospitalizations in coastal cities and substantial heat burdens in the Central Valley. Diurnal heat events had the greatest impact in the Central Valley, while nighttime extreme heat events drove burdens in the southeastern desert. This spatially informed approach guides local policies, prioritizing dangerous heat events to reduce the heat-health burden. The methodology is applicable to other regions, informing early warning systems and characterizing extreme heat impacts.

Unraveling local and regional determinants of high plant diversity at marine rocky outcrops in Uruguay

AbstractQuestionsMarine rocky outcrops are model systems of community assembly under harsh conditions. The prevailing environmental conditions that determine a coast–inland gradient of stress and disturbance impose a strong environmental filter on community assembly. However, the Atlantic rocky outcrops of Uruguay challenge this assumption as they exhibit high plant diversity at small spatial scales. We investigated this study system to answer: (1) which environmental factors determine diversity at the local scale; (2) and how does the regional pool influence species composition along the coast–inland gradient?MethodsWe analyzed the local and regional determinants of plant community assembly in four rocky sites along the Uruguayan coast. Through a random sampling approach stratified by distance to the coast, we recorded species occurrences and microenvironmental conditions. Observed taxa were assigned into different species assemblages according to their typical vegetation type. Generalized Linear Model (GLM)–Poisson regression, quantile regressions and hierarchical cluster analyses were used to identify the factors underlying local richness and the spatial vegetation structure.ResultsNine different vegetation types generate a mass effect that enhances local diversity. Unexpectedly, 56% of the species are from non‐marine environments — e.g. grasslands or hydrophilous herblands. Species assemblages were spatially clustered, with a turnover of these clusters along the coast–inland gradient. Elevation, distance to the coast and vegetation cover promoted richness, likely due to an attenuation of marine filters. Meanwhile, substrate availability reduced richness, likely due to competitive exclusion as a result of more resources and homogeneous microenvironmental conditions.ConclusionsThe high local diversity along the marine rocky outcrops of Uruguay is best explained by a functionally diverse regional species pool, which interacts with local heterogeneity, and by conditions that enhance or attenuate the effect of marine stress. Effective conservation and management strategies are key to minimize the detrimental effects of urbanization, fragmentation, and non‐native plant invasions on these diverse habitats.

Canopy cover and soil moisture influence forest understory plant responses to experimental summer drought.

Extreme droughts are globally increasing in frequency and severity. Most research on drought in forests focuses on the response of trees, while less is known about the impacts of drought on forest understory species and how these effects are moderated by the local environment. We assessed the impacts of a 45-day experimental summer drought on the performance of six boreal forest understory plants, using a transplant experiment with rainout shelters replicated across 25 sites. We recorded growth, vitality and reproduction immediately, 2 months, and 1 year after the simulated drought, and examined how differences in ambient soil moisture and canopy cover among sites influenced the effects of drought on the performance of each species. Drought negatively affected the growth and/or vitality of all species, but the effects were stronger and more persistent in the bryophytes than in the vascular plants. The two species associated with older forests, the moss Hylocomiastrum umbratum and the orchid Goodyera repens, suffered larger effects than the more generalist species included in the experiment. The drought reduced reproductive output in the moss Hylocomium splendens in the next growing season, but increased reproduction in the graminoid Luzula pilosa. Higher ambient soil moisture reduced some negative effects of drought on vascular plants. Both denser canopy cover and higher soil moisture alleviated drought effects on bryophytes, likely through alleviating cellular damage. Our experiment shows that boreal understory species can be adversely affected by drought and that effects might be stronger for bryophytes and species associated with older forests. Our results indicate that the effects of drought can vary over small spatial scales and that forest landscapes can be actively managed to alleviate drought effects on boreal forest biodiversity. For example, by managing the tree canopy and protecting hydrological networks.

EL-YOLO: An efficient and lightweight low-altitude aerial objects detector for onboard applications

Existing deep learning-based low-altitude small object detectors are typically complex in model architecture and demand substantial computational resources, making deployment for real-time detection tasks on edge computing devices challenging. To address this issue, we proposed EL-YOLO, an efficient and lightweight onboard applications object detector. Initially, in order to maintain a lightweight design and improve model accuracy, we propose a novel approach called Sparsely Connected Asymptotic Feature Pyramid Network(SCAFPN). This approach aims to eliminate inter-layer interference during feature fusion, thereby enhancing the model’s performance. Furthermore, to establish long-range contextual relationships for small object scale information, we devise a Cross-Space Learning Multi-Head Self-Attention mechanism (CSL-MHSA). To assess EL-YOLO capability for onboard small object detection, we deploy it on the embedded NVIDIA Jetson Xavier Nx platform and employ NVIDIA TensorRT FP16 quantization acceleration. On the VisDrone2019-DET and AI-TOD datasets, EL-YOLO demonstrates a 12.4% and 1.3% improvement in mAP50 compared to YOLOv5s. In comparison with the state-of-the-art YOLOv8s proposed in 2023, it achieves a respective 2.8% and 10.7% increase in mAP50. Moreover, the inference speed for the Small model reaches 24 frames per second, while the Nano model achieves 35 frames per second. This method holds promise for direct integration onto unmanned aerial vehicles for aerial small object detection tasks in the future.