Hasil untuk "General. Including nature conservation, geographical distribution"

Abhipsa Basu, Mohana Singh, Shashank Agnihotri et al.

Text-to-image (T2I) models are rapidly gaining popularity, yet their outputs often lack geographical diversity, reinforce stereotypes, and misrepresent regions. Given their broad reach, it is critical to rigorously evaluate how these models portray the world. Existing diversity metrics either rely on curated datasets or focus on surface-level visual similarity, limiting interpretability. We introduce GeoDiv, a framework leveraging large language and vision-language models to assess geographical diversity along two complementary axes: the Socio-Economic Visual Index (SEVI), capturing economic and condition-related cues, and the Visual Diversity Index (VDI), measuring variation in primary entities and backgrounds. Applied to images generated by models such as Stable Diffusion and FLUX.1-dev across $10$ entities and $16$ countries, GeoDiv reveals a consistent lack of diversity and identifies fine-grained attributes where models default to biased portrayals. Strikingly, depictions of countries like India, Nigeria, and Colombia are disproportionately impoverished and worn, reflecting underlying socio-economic biases. These results highlight the need for greater geographical nuance in generative models. GeoDiv provides the first systematic, interpretable framework for measuring such biases, marking a step toward fairer and more inclusive generative systems. Project page: https://abhipsabasu.github.io/geodiv

Daniel Collins, Carolina Moreira Ferrera, Ismael L. Paiva et al.

We show that networks of quantum frames of reference, in which one frame may be used to produce multiple other frames that in their turn prepare systems which may interact with one another, have counterintuitive properties that make following the exchange of conserved quantities very subtle, and raise questions about the very nature of conserved quantities. In addition, we present an alternative approach to analysing quantum reference frames that we believe will be useful in discussions related to quantum frames of reference.

Tom Burgert, Leonard Hackel, Paolo Rota et al.

Self-supervised learning (SSL) has become a powerful paradigm for learning from large, unlabeled datasets, particularly in computer vision (CV). However, applying SSL to multispectral remote sensing (RS) images presents unique challenges and opportunities due to the geographical and temporal variability of the data. In this paper, we introduce GeoRank, a novel regularization method for contrastive SSL that improves upon prior techniques by directly optimizing spherical distances to embed geographical relationships into the learned feature space. GeoRank outperforms or matches prior methods that integrate geographical metadata and consistently improves diverse contrastive SSL algorithms (e.g., BYOL, DINO). Beyond this, we present a systematic investigation of key adaptations of contrastive SSL for multispectral RS images, including the effectiveness of data augmentations, the impact of dataset cardinality and image size on performance, and the task dependency of temporal views. Code is available at https://github.com/tomburgert/georank.

Krešimir Kušić, Vinny Cahill, Ivana Dusparic

The operational effectiveness of digital-twin technology in motorway traffic management depends on the availability of a continuous flow of high-resolution real-time traffic data. To function as a proactive decision-making support layer within traffic management, a digital twin must also incorporate predicted traffic conditions in addition to real-time observations. Due to the spatio-temporal complexity and the time-variant, non-linear nature of traffic dynamics, predicting motorway traffic remains a difficult problem. Sequence-based deep-learning models offer clear advantages over classical machine learning and statistical models in capturing long-range, temporal dependencies in time-series traffic data, yet limitations in forecasting accuracy and model complexity point to the need for further improvements. To improve motorway traffic forecasting, this paper introduces a Geographically-aware Transformer-based Traffic Forecasting GATTF model, which exploits the geographical relationships between distributed sensors using their mutual information (MI). The model has been evaluated using real-time data from the Geneva motorway network in Switzerland and results confirm that incorporating geographical awareness through MI enhances the accuracy of GATTF forecasting compared to a standard Transformer, without increasing model complexity.

Jean‐Nicolas Pradervand, Florian Zellweger, Jérémy Gremion et al.

Human‐induced alterations in natural water flow have seriously impaired the integrity of riverine ecosystems. Nonetheless, even in human‐altered riverine and adjacent terrestrial habitats, there is considerable potential for the protection of rare species if management practices prioritize biodiversity conservation. However, the management of such areas often presents complex challenges. On the one hand, efforts to mitigate natural hazards frequently overshadow biodiversity conservation objectives. On the other hand, high‐resolution maps of forest structures are often lacking but could be very useful for spatial prioritization of conservation efforts, especially as vegetation structure can be directly managed through local restoration activities. Here, we used an airborne LiDAR‐derived vegetation structure along an 80 km stretch of the Rhône River (Valais, Switzerland) to assess the habitat characteristics that best explain the presence of a flagship species, the common nightingale Luscinia megarhynchos, a species that historically thrived along this river system but has experienced a drastic population decline over the past decades. Nightingales showed a preference for dense vegetation in the lower strata above ground (3–6 m), as opposed to an open and sparsely vegetated ground level (0–1 m). The preferred habitats were predominantly located within forested regions, as indicated by a preference for taller canopies. These findings align surprisingly well with prior field research on the species, demonstrating the capability of high‐resolution LiDAR to upscale locally derived habitat preferences across very large areas. Based on LiDAR outputs, we proposed management recommendations for the whole river. Such spatially detailed information furthers our understanding of local habitat preferences of endangered species, thus facilitating the formulation of conservation recommendations at the scale of entire populations.

Qi Peng, Shuichiro Yokoyama, Kiyotomo Ichiki

A modification to the vis-viva equation that accounts for general relativistic effects is introduced to enhance the accuracy of predictions of orbital motion and precession. The updated equation reduces to the traditional vis-viva equation under Newtonian conditions and is a more accurate tool for astrodynamics than the traditional equation. Preliminary simulation results demonstrate the application potential of the modified vis-viva equation for more complex n-body systems. Spherical symmetry is assumed in this approach; however, this limitation could be removed in future research. This study is a pivotal step toward bridging classical and relativistic mechanics and thus makes an important contribution to the field of celestial dynamics.

Sang-Ah Lee, Sang-Ah Lee, Chang Seon Ryu et al.

Reports have shown an increase in the use of disinfectants in wastewater treatment plants, prompted by the detection of residual viruses in sewage. However, the release of disinfection byproducts (DBPs) in final effluents has raised concerns about their potential adverse effects, such as endocrine disruption, on aquatic environments. Despite these concerns, few studies have examined the endocrine-disrupting effects of DBPs on fish, which may be vulnerable to DBPs. The aim of this case study was to investigate the endocrine-disrupting properties of four commonly formed DBPs: chloroiodomethane (CIM), dibromochloromethane (DBCM), bromodichloromethane (BDCM), and trichloroacetic acid (TCA) on the estrogen receptor-α in zebrafish (zERα). The results indicated that all four DBPs have high anti-estrogenic activity against zERα; with CIM, BDCM, DBCM, and TCA yielding 80.8%, 78.4%, 49.0%, and 64.1% anti-estrogenic effects on zERα, respectively. Moreover, all DBPs demonstrated negligible estrogenic effects on zERα. Our study sheds new light on the adverse effects of DBPs, particularly the endocrine-disrupting activity of CIM, which, as part of the dihalomethanes group, has received limited research attention in the past. This study shows the molecular interactions in terms of the endocrine disruption of DBP on zERα, warranting further studies to understand the overall impact of fish in affected aquatic ecosystems.

Ana Elisa Cabral, Felisa Rey, Felisa Rey et al.

Syngnathids (seahorses, pipefishes and seadragons) are an attractive resource for Traditional Chinese Medicine (TCM). Despite few scientific studies supporting seahorse nutritional benefits, they are believed to possess medicinal properties that enhance human health. The European short-snout seahorse Hippocampus hippocampus is classified as Data Deficient by the IUCN Red List of Threatened Species. Nevertheless, there are increasing records of this species being illegally captured and traded to supply TCM. This study investigated the fatty acid (FA) profiles of the trunk muscles of cultured female and male H. hippocampus, to assess sex and intraspecific variation, as well as their potential nutritional value. The contents of crude lipid (4.05 ± 2.15% dry weight, DW in females and 2.82 ± 1.48% DW in males) and phospholipid (8.23 ± 3.34 μg mg−1 DW in females and 7.91 ± 2.36 μg mg−1 DW in males) were not significantly different between the two sexes. The absolute FA compositions of H. hippocampus trunk muscles revealed higher mean values for FA 16:0, 18:0, 18:1 n-9 and 22:6 n-3 (DHA), in both female (2.82 ± 1.11, 1.81 ± 0.89, 0.90 ± 0.41 and 0.93 ± 0.35 μg mg−1 DW, respectively) and male specimens (1.99 ± 0.95, 1.52 ± 0.78, 0.74 ± 0.44 and 0.80 ± 0.41 μg mg−1 DW, respectively). In terms of FA classes, saturated fatty acids (SFA) showed the highest absolute value of the total pool of FA, for both sexes (4.73 ± 1.94 μg mg−1 DW in females and 3.58 ± 1.76 μg mg−1 DW in males). Males tended to exhibit a more suitable profile for human nutrition, displaying a lower atherogenic index (AI) and thrombogenic index (TI). The relative composition of H. hippocampus trunk muscles followed the patterns of seahorse species valued in TCM, with DHA ranking amongst the PUFA with higher mean relative abundances (12.0% of total FA). While seahorse FA profiles may be of interest in terms of their nutritional value for humans, only specimens originating from sustainable production practices should be traded and the conservation of their populations in the wild should continue to be a global priority.

Kristian Ions, Khan Ozdemir, Douglas Pender et al.

Gravel barrier beaches can offer natural protection to coastlines from adverse storm conditions. Understanding the morphodynamics of gravel barrier beaches is vital for the effective and sustainable management of these systems. Here, we use a synthetic dataset to investigate the morphodynamic response of the gravel barrier beach at Hurst Castle Spit, located on the Southwest coast of the United Kingdom, to both unimodal and bimodal storms. This spit is exposed to wind and swell waves propagating up the English Channel from the Southwest approaches and has suffered repeated storm erosion. The results are analyzed to identify the key drivers that govern the spatio-temporal gravel barrier morphodynamic responses to storms and to explore the morphodynamic states of the barrier. We found that the morphodynamic response of the barrier beach is strongly influenced by the combination of storm wave height and still water level. Further, the presence of swell waves can be a controlling factor in the barrier response.

Tao Liu, Xiaofei Shang, Yuanyuan Su et al.

[Objective] Green utilization efficiency of cultivated land in the lower Yellow River and its convergence and influencing factors were analyzed in order to provide a reference for ecological protection and high-quality development of cultivated land in the lower Yellow River. [Methods] Undesirable outputs such as surface pollution and carbon emissions from cultivated land, and the carbon sequestration and sink capacity of cultivated land resources were simultaneously incorporated into the evaluation index system. The green utilization efficiency, convergence, and influencing factors of cultivated land in 34 municipalities in the lower Yellow River from 2007 to 2020 were systematically analyzed using the EBM model, the convergence model, and the panel random effects Tobit model. [Results] ① The green utilization efficiency of cultivated land in the lower Yellow River showed an overall upward trend, but still did not reach the optimal state by the end of 2020. The green utilization efficiency of cultivated land in the lower Yellow River was spatially unbalanced. The green utilization efficiency of cultivated land in Southern He’nan and Northern Shandong provinces was high, while that in Zhengzhou, Weihai, and other cities was always low. ② From the perspective of efficiency decomposition, the main driving force for the improvement of green utilization efficiency of cultivated land in the lower Yellow River was scale efficiency, while the resistance came from pure technical efficiency. ③ From the convergence test, both σ convergence and β convergence existed in the green utilization efficiency of farmland in the lower Yellow River. The inter-city gap of cultivated land green utilization efficiency in He’nan Province was obviously lower than in Shandong Province, but the convergence rate in Shandong Province was faster. ④ In terms of influencing factors, crop planting structure and government financial support to agriculture increased green utilization efficiency of cultivated land in the lower Yellow River, while the urban-rural income gap, economic development level, and farmland machinery input intensity decreased green utilization efficiency. [Conclusion] In the future, the lower Yellow River should not only improve the comprehensive management level of the green utilization of cultivatedpland and strengthen inter-city exchanges and cooperation, but should also focus on the coordination between the convergence rate of green utilization efficiency of cultivated land and the development gap in each region while promoting development of the green utilization of cultivated land.

Athanase Papadopoulos

These are notes on the impact of Lagrange's memoir on the construction of geographical maps. We mention the relations of some ideas and questions introduced in this memoir with other notions that appeared later in the works of several mathematicians, including in particular Chebyshev (19th c.) and Darboux (19th-20th c.), two mathematicians who were particularly interested in geography.

Andrew Schulz, Cassie Shriver, Suzanne Stathatos et al.

The recent increase in public and academic interest in preserving biodiversity has led to the growth of the field of conservation technology. This field involves designing and constructing tools that utilize technology to aid in the conservation of wildlife. In this article, we will use case studies to demonstrate the importance of designing conservation tools with human-wildlife interaction in mind and provide a framework for creating successful tools. These case studies include a range of complexities, from simple cat collars to machine learning and game theory methodologies. Our goal is to introduce and inform current and future researchers in the field of conservation technology and provide references for educating the next generation of conservation technologists. Conservation technology not only has the potential to benefit biodiversity but also has broader impacts on fields such as sustainability and environmental protection. By using innovative technologies to address conservation challenges, we can find more effective and efficient solutions to protect and preserve our planet's resources.

Katarzyna Melaniuk, Kamila Sztybor, Tina Treude et al.

This paper presents the results of a study on the response of living benthic foraminifera to progressing environmental successions in a cold-seep ecosystem. Sediment samples were collected from Vestnesa Ridge (79°N, Fram Strait) at ~1200 m water depth. The distribution of live (Rose Bengal-stained) foraminifera were analyzed in the upper sediment layers in relation to pore water biogeochemical data together with the distribution of sulfur-bacterial mats and Siboglinidae tubeworms. At methane cold seeps, the process of environmental succession is strongly connected to the duration and strength of methane seepage and the intensity of methane-related biological processes, e.g, aerobic and anaerobic oxidation of methane (MOx and AOM, respectively). The results show that the distribution patterns of benthic foraminifera change according to the progressing environmental succession. The benthic foraminifera seemed to thrive in sediments with a moderate activity of seepage, dominated by MOx, i.e, at an early stage of seepage or when seepage decreases at a late stage of the succession. Species composition of the foraminiferal fauna under these conditions was similar to the control sites (outside of pockmarks with no seepage); the dominant species being Melonis barleeanus and Cassidulina neoteretis. In sediments with strong seepage and high AOM activity, the hostile environmental conditions due to the presence of toxic sulfide caused a reduction in the foraminiferal population, and samples were almost barren of foraminifera. In environments of moderate methane seepage, the presence of chemosynthetic Siboglinidae tube worms potentially support communities of the epibenthic species Cibicidoides wuellerstorfi. Despite the very different environmental conditions, the foraminiferal assemblages were very similar (or nearly absent). Therefore, the foraminiferal faunas cannot be used as exclusive indicators of past strength of methane seepage in palaeoceanographic interpretations.

Igor Khorozyan

The literature other than scientific journals (non-journals) is a valuable, but scattered and rarely used, source of evidence of the effectiveness of interventions applied for protection from mammalian predators. This study describes how journals and non-journals differ in relation to study designs, types of interventions, predator species, countries, and publication bias. I collected 411 journal cases (226 publications) and 97 non-journal cases (64 publications) covering the period 1955–2020, five study designs, six interventions, 28 species and 50 countries. Non-journals were important for two predators (leopard Panthera pardus and snow leopard P. uncia) and four countries (Canada, India, Russia and Sri Lanka). These species and countries have been affected by human-predator conflicts and the use of non-journals should become a habitual practice to mitigate conflicts. Information on other species and countries, and all study designs and interventions, was provided mostly or only in peer-reviewed journals. This study helps make the use of non-journals easier for researchers and conservation practitioners by providing and explaining a list of relevant literature and online resources.

Martin Jakobsson, Larry A. Mayer

The ocean and the marine parts of the cryosphere interact directly with, and are affected by, the seafloor and its primary properties of depth (bathymetry) and shape (morphology) in many ways. Bottom currents are largely constrained by undersea terrain with consequences for both regional and global heat transport. Deep ocean mixing is controlled by seafloor roughness, and the bathymetry directly influences where marine outlet glaciers are susceptible to the inflow relatively warm subsurface waters - an issue of great importance for ice-sheet discharge, i.e., the loss of mass from calving and undersea melting. Mass loss from glaciers and the Greenland and Antarctic ice sheets, is among the primary drivers of global sea-level rise, together now contributing more to sea-level rise than the thermal expansion of the ocean. Recent research suggests that the upper bounds of predicted sea-level rise by the year 2100 under the scenarios presented in IPCC’s Special Report on the Ocean and Cryosphere in a Changing Climate (SROCCC) likely are conservative because of the many unknowns regarding ice dynamics. In this paper we highlight the poorly mapped seafloor in the Polar regions as a critical knowledge gap that needs to be filled to move marine cryosphere science forward and produce improved understanding of the factors impacting ice-discharge and, with that, improved predictions of, among other things, global sea-level. We analyze the bathymetric data coverage in the Arctic Ocean specifically and use the results to discuss challenges that must be overcome to map the most remotely located areas in the Polar regions in general.

Shilong Liu, Yingwen Zhang, Boris A. Malomed et al.

The fractional Schrödinger equation (FSE) -- a natural extension of the standard Schrödinger equation -- is the basis of fractional quantum mechanics. It can be obtained by replacing the kinetic-energy operator with a fractional derivative. Here, we report the experimental realisation of an optical FSE for femtosecond laser pulses in the temporal domain. Programmable holograms and the single-shot measurement technique are respectively used to emulate a \textit{Lévy waveguide} and to reconstruct the amplitude and phase of the pulses. Varying the Lévy index of the FSE and the initial pulse, the temporal dynamics is observed in diverse forms, including solitary, splitting and merging pulses, double Airy modes, and ``rain-like'' multi-pulse patterns. Furthermore, the transmission of input pulses carrying a fractional phase exhibits a ``fractional-phase protection'' effect through a regular (non-fractional) material. The experimentally generated fractional time-domain pulses offer the potential for designing optical signal-processing schemes.

Sufang Wang, Xiaopei Yu, Shunqin Zhang et al.

Beyond its role as an oxygen transport protein, the homodimer hemoglobin of blood clam Tegillarca granosa (Tg-HbI) has been found to possess antibacterial activity. However, the mechanism of antibacterial activity of Tg-HbI remain to be investigated. In this study, we investigated the effects of Cu2+ on the structure, peroxidase activity, and antibacterial ability of Tg-HbI. Tg-HbI was significantly inactivated by Cu2+ in a non-competitive inhibition manner, following first-order reaction kinetics. The Spectroscopy results showed that Cu2+ changed the iron porphyrin ring and the coordination of heme with proximal histidine of Tg-HbI, and increased the hydrophobicity of heme pocket. We found that proline could stabilize the heme pocket structure of Tg-HbI, hence, protect peroxidase activity and antimicrobial activity of Tg-HbI against damage by Cu2+. Our results suggest that Cu2+ inhibits the peroxidase and antibacterial activity of Tg-HbI by destroying its heme pocket structure and Tg-HbI probably plays an antibacterial role through its peroxidase activity. This result could provide insights into the antibacterial mechanism of Tg-HbI.

Albertina Dias, Albertina Dias, Siby Kurian et al.

Colored dissolved organic matter (CDOM) is one of the important fractions of dissolved organic matter (DOM) that controls the availability of light in water and plays a crucial role in the cycling of carbon. High CDOM absorption in the Mandovi Estuary (Goa) during spring inter-monsoon (SIM) is largely driven by both in-situ production and anthropogenic activities. Here we have presented the CDOM variation in the estuary during SIM of 2014–2018 and compared it with that of 2020 when the COVID-19 outbreak imposed lockdown was implemented. During 2020, low CDOM absorption was observed at the mid-stream of the estuary as compared to the previous years, which could be attributed to low autochthonous production and less input from anthropogenic activities. On the other hand, high CDOM observed at the mouth during 2020 is linked to autochthonous production, as seen from the high concentrations of chlorophyll a. High CDOM in the upstream region could be due to both autochthonous production and terrestrially derived organic matter. Sentinel-2 satellite data was also used to look at the variations of CDOM in the study region which is consistent with in-situ observations. Apart from this, the concentration of nutrients (NO3–, NH4+, and SiO44–) in 2020 was also low compared to the previous reports. Hence, our study clearly showed the impact of anthropogenic activities on CDOM build-up and nutrients, as the COVID-19 imposed lockdown drastically controlled such activities in the estuary.

Jingyan Zhang, Jingyan Zhang, Mengqian Zhang et al.

Ammonia is a common environmental stressor encountered during aquaculture, and is a significant concern due to its adverse biological effects on vertebrate and invertebrate including crustaceans. However, little information is available on physiological and molecular responses in crustaceans under long-term ammonia exposure, which often occurs in aquaculture practices. Here, we investigated temporal physiological and molecular responses in the gills, the main ammonia excretion organ, of the swimming crab Portunus trituberculatus following long-term (4 weeks) exposure to three different ammonia nitrogen concentrations (2, 4, and 8 mg l–1), in comparison to seawater (ammonia nitrogen below 0.03 mg l–1). The results revealed that after ammonia stress, the ammonia excretion and detoxification pathways were initially up-regulated. These processes appear compromised as the exposure duration extended, leading to accumulation of hemolymph ammonia, which coincided with the reduction of adenosine 5′-triphosphate (ATP) and adenylate energy charge (AEC). Considering that ammonia excretion and detoxification are highly energy-consuming, the depression of these pathways are, at least partly, associated with disruption of energy homeostasis in gills after prolonged ammonia exposure. Furthermore, our results indicated that long-term ammonia exposure can impair the antioxidant defense and result in increased lipid peroxidation, as well as induce endoplasmic reticulum stress, which in turn lead to apoptosis through p53-bax pathway in gills of the swimming crab. The findings of the present study further our understanding of adverse effects and underlying mechanisms of long-term ammonia in decapods, and provide valuable information for aquaculture management of P. trituberculatus.

Wenyuan Li, Keyan Chen, Hao Chen et al.

The proliferation of remote sensing satellites has resulted in a massive amount of remote sensing images. However, due to human and material resource constraints, the vast majority of remote sensing images remain unlabeled. As a result, it cannot be applied to currently available deep learning methods. To fully utilize the remaining unlabeled images, we propose a Geographical Knowledge-driven Representation learning method for remote sensing images (GeoKR), improving network performance and reduce the demand for annotated data. The global land cover products and geographical location associated with each remote sensing image are regarded as geographical knowledge to provide supervision for representation learning and network pre-training. An efficient pre-training framework is proposed to eliminate the supervision noises caused by imaging times and resolutions difference between remote sensing images and geographical knowledge. A large scale pre-training dataset Levir-KR is proposed to support network pre-training. It contains 1,431,950 remote sensing images from Gaofen series satellites with various resolutions. Experimental results demonstrate that our proposed method outperforms ImageNet pre-training and self-supervised representation learning methods and significantly reduces the burden of data annotation on downstream tasks such as scene classification, semantic segmentation, object detection, and cloud / snow detection. It demonstrates that our proposed method can be used as a novel paradigm for pre-training neural networks. Codes will be available on https://github.com/flyakon/Geographical-Knowledge-driven-Representaion-Learning.