Distribution Information Research Articles

Ground Constrained 3D Lidar SLAM Design and Implementation

Abstract. Synchronized positioning and mapping techniques based on multi-line LIDAR are mainly used for mobile platforms that require high-precision positioning, such as UAVs and self-driving cars. However, multi-line LiDAR is limited by vertical field of view and vertical angular resolution, which can affect the vertical accuracy of attitude estimation. In this paper, we aim to extract the ground information in the environment and fuse it into a factor map to constrain the vertical accuracy of the attitude. Different from the traditional geometric information-based ground plane segmentation, this paper utilizes point cloud distribution information to extract the ground cloud and uses high-confidence ground features to constrain the attitude drift by considering their distribution weights. Finally, the laser range factor, ground constraint factor and closed-loop factor are integrated under the factor graph optimization framework. The effectiveness of the method is validated on a self-constructed dataset.

Fruit Distribution Density Estimation in YOLO-Detected Strawberry Images: A Kernel Density and Nearest Neighbor Analysis Approach

Precise information on strawberry fruit distribution is of significant importance for optimizing planting density and formulating harvesting strategies. This study applied a combined analysis of kernel density estimation and nearest neighbor techniques to estimate fruit distribution density from YOLOdetected strawberry images. Initially, an improved yolov8n strawberry object detection model was employed to obtain the coordinates of the fruit centers in the images. The results indicated that the improved model achieved an accuracy of 94.7% with an mAP@0.5~0.95 of 87.3%. The relative error between the predicted and annotated coordinates ranged from 0.002 to 0.02, demonstrating high consistency between the model predictions and the annotated results. Subsequently, based on the strawberry center coordinates, the kernel density estimation algorithm was used to estimate the distribution density in the strawberry images. The results showed that with a bandwidth of 200, the kernel density estimation accurately reflected the actual strawberry density distribution, ensuring that all center points in high-density regions were consistently identified and delineated. Finally, to refine the strawberry distribution information, a comprehensive method based on nearest neighbor analysis was adopted, achieving target area segmentation and regional density estimation in the strawberry images. Experimental results demonstrated that when the distance threshold ϵ was set to 600 pixels, the correct grouping rate exceeded 94%, and the regional density estimation results indicated a significant positive correlation between the number of fruits and regional density. This study provides scientific evidence for optimizing strawberry planting density and formulating harvesting sequences, contributing to improved yield, harvesting efficiency, and reduced fruit damage. In future research, this study will further explore dynamic models that link fruit distribution density, planting density, and fruit growth status.

Contribution to the Study of Malagasy Orchids. XXXIX. Two New Species of Bulbophyllum from Madagascar

Two new species of Bulbophyllum Thouars, B. psittacinum Verlynde & Ramand. and B. vespertilioides Verlynde & Ramand. (Orchidaceae), are recognized and described. Both species are endemic to Madagascar and were found in the Ankerana forest, part of the Ankeniheny-Zahamena corridor (CAZ) protected area in the eastern escarpment forests. These two species belong to section Pantoblepharon Schltr.; B. psittacinum differs from the rest of the section by its conjoined lateral sepals and B. vespertilioides by its larger pseudobulbs, longer inflorescence, and number of flowers. Taxonomic treatments of both species with descriptions, illustrations, distribution, and habitat information as well as preliminary IUCN Red List assessments are provided.

Enhanced Speech Processing for Air Traffic Control Using an Optimized Generative Adversarial Network

In order to improve the quality of voice calls during air traffic control, an improved SEGAN air traffic control speech enhancement algorithm is proposed. Aiming at the problem that the traditional speech enhancement algorithm based on generative adversarial network (SEGAN) is drowned under low signal-to-noise ratio conditions, a multi-stage, multi-mapping, multi-dimensional output generator and a multi-scale, multi-discriminator network model are proposed based on the SEGAN network model. First, the speech semantic features are extracted based on the deep neural network structure to complete the semantic segmentation of air traffic control speech. Secondly, multiple generators are set to further optimize the speech signal. Then, a downsampling module is added to the convolution layer to improve the model's utilization of speech information and reduce the loss of speech information. Finally, multi-scale, multiple discriminators are used to learn the distribution law and information of speech samples in multiple directions. The results show that under low signal-to-noise ratio conditions, the improved SEGAN model improves the short-term objective intelligibility (STOI) and the perceptual evaluation of speech quality (PESQ) by and respectively , which can quickly and effectively perform air traffic control speech enhancement and provide preparation for subsequent air traffic control speech recognition.

The non-exponential decay characteristics of HTS NI-class coils in sudden discharge experiments

Abstract The decay of the voltage and magnetic field of the high-temperature superconductivity (HTS) no-insulation-class (NI-class) coil in the sudden discharge experiment is usually considered to be exponential. However, our experiment found that it is not accurate to describe the decay characteristics of the NI-class coil with a simple exponential function. Combined with equivalent circuit models of the NI-class coil, we use the theory of ordinary differential equations to explain the non-exponential decay characteristics and point out that it is closer to the matrix exponential characteristics. Based on this finding, we believe that the non-uniform turn-to-turn contact resistivity (TTCR) is an important cause of the non-exponential decay characteristics of the NI-class coil. Reverse thinking leads us to realize that the voltage decay curve of the NI-class coil in the sudden discharge experiment contains the distribution information of its TTCR. Therefore, we propose a method for measuring the TTCR of NI-class coils based on the matrix exponential model. The co-simulation combining the finite element model and the equivalent circuit model shows that the non-uniformly distributed TTCR has a great influence on the transient process of the NI-class coil, which makes the current and current density in the transient process vary greatly in different regions of the NI-class coil. Those findings mean that the simulation study of the NI-class coils and magnets with uniform TTCR usually used in the past may be far from the actual situation.

Distribution extension of a vent scale worm Branchinotoglumabipapillata (Polychaeta, Polynoidae) in the Indian Ocean.

Branchinotogluma Pettibone, 1985 is the most species-rich genus within the subfamily Lepidonotopodinae Pettibone, 1983, comprising 18 valid species from chemosynthesis-based ecosystems in the Pacific and Indian Oceans. Here, we report a new distributional record of Branchinotoglumabipapillata Zhou, Wang, Zhang & Wang, 2018, at the hydrothermal vent sites on the northern Central Indian Ridge (nCIR). This record represents the northernmost occurrence of B.bipapillata in the Indian Ocean. We conducted a comparative study of the nCIR population and other documented populations using distributional information, morphological traits, and genetic markers (two mitochondrial [COI, 16S rRNA] and one nuclear [18S rRNA] genes). While most morphological characters of B.bipapillata were consistent with those found in the Southwest Indian Ridge (SWIR), variations were noted in the segment with the last branchiae. Molecular data revealed that all populations of B.bipapillata form a single clade, indicating a wide distribution from the SWIR to nCIR, covering ~4,000 km across various ridges in the Indian Ocean. This study presents extensive distribution of a vent species with well-connected populations throughout the Indian Ocean, distinguishing it from many other vent species affected by the dispersal barrier in the Indian Ocean.

Research on planting planning of Glycyrrhiza uralensis in Naiman Banner based on MaxEnt model and remote sensing technology

Benefits of Glycyrrhiza uralensis include removing heat, detoxifying, and moistening the lungs, easing coughs, refueling the spleen, and balancing medications. In addition to providing theoretical guidance for the development of the G. uralensis industry and rural revitalization plan, it is anticipated that this paper will also provide basic data for the formulation of production layout of the G. uralensis industry at the county level, the control of cultivation industry direction, the establishment of high-quality G. uralensis cultivation technology system. The Maximum Entropy (MaxEnt) model was used to simulate the potential distribution of G. uralensis, a Chinese medicine resource, in Naiman Banner. By conducting a field inquiry and a broad assessment of the available Chinese medicine resources, the distribution information was acquired. The random forest technique was used to classify G. uralensis. The phenological cycle and development mode of vegetation, which exhibits diverse temporal traits and aids in identification, were elucidated through long-term series analysis. The random forest classification algorithm based on multiple features showed high accuracy in remote sensing (RS) recognition of G. uralensis. Comparative analysis of the MaxEnt and RS results showed that the planting area of G. uralensis was smaller than that of its potential distribution. The expansion to high-suitability areas planting should be prioritized. Based on the dual analysis of regional and remote sensing, it not only proved the great potential of using geographic information to predict the distribution of G. uralensis, but also verified the great potential of extracting the distribution of G. uralensis from GF-6 images. These results will guide the planting and development of G. uralensis in Naiman Banner and a scientific basis for the development of G. uralensis economy, conducive to optimizing the ecological environment and promoting rural revitalization programs.

Fan noise radial mode detection based on [formula omitted] regularization method

Radial mode detection has been widely employed in fan noise research. Many radial mode detection algorithms by conducting the convex L1 norm optimization have been proposed by taking advantage of the fact that the fan noise sound field is usually dominated by a limited set of radial modes. Nevertheless, L1 norm optimization has been shown to be suboptimal and cannot enforce further sparsity. A fan noise radial mode detection method based on L1/2 regularization algorithm is proposed in this paper to improve its robustness and dynamic range. This method employs the L1/2 regularization to directly solve the in-duct sound propagation model. Synthesized simulations indicates that the L1/2 regularization method can detect the correct radial mode order and amplitude under low signal-to-noise ratio. Moreover, the new method is insensitive to regularization parameter. An experimental system of radial rake is implemented to validate the new method. It is shown that the L-curve method, which do not require any prior information of the acoustic mode distribution or contaminating measurement noise, is an appropriate choice of the regularization parameter determination method for the L1/2 regularizer. It is demonstrated that the new L1/2 regularization method can enhance the mode sparsity, especially under low signal-to-noise ratio. Moreover, the resolution and dynamic range can be improved by the L1/2 regularization method, which makes it an effective and robust fan noise radial mode detection technique in practical applications.

A taxonomic revision of Tillandsia (Tillandsioideae, Bromeliaceae) from Uruguay

A taxonomic revision of the genus Tillandsia (Bromeliaceae) from Uruguay is here presented based on the examination of herbarium specimens, field surveys, and an extensive analysis of taxonomic literature. Nineteen taxa are recognized: 17 species, one subspecies, and one natural hybrid. A new identification key for all the species of Tillandsia occurring in the country is presented. Data on nomenclature (correct names, types, synonyms used in Uruguay) are provided for each taxon, along with detailed morphological descriptions, vernacular names, distribution and habitat information (global and local), phenology, conservation assessment, diagnostic characters, and nomenclatural and taxonomical notes. This information is complemented with images, illustrations of floral parts, maps showing species distribution in Uruguay, and a phenological diagram. Tillandsia arequitae and T. uruguayensis are endemic to Uruguay, and five species reach their southern limit of distribution in the country (T. bandensis, T. geminiflora, T. ixioides, T. loliacea, and T. stricta). Tillandsia capillaris and T. virescens are registered as exotic and subspontaneous. A new natural hybrid between T. aëranthos and T. recurvifolia is described. Three species previously cited for Uruguay (T. crocata, T. lorentziana, and T. streptocarpa) are excluded or cited as doubtful species for the country. Tillandsia bicolor is discarded as a synonym of T. aëranthos, and T. dianthoidea is considered for the first time as an illegitimate superfluous name. Lectotypes for Tillandsia arequitae (second-step), T. capillaris, T. circinalis (second-step), T. cordobensis (second-step), T. duratii, T. geminiflora (second-step), T. hieronymi (second-step), T. ixioides, T. microxiphion, T. recurvata, T. stricta (second-step), T. tricholepis (second-step) and T. virescens, as well as an epitype for T. aëranthos are designated.

Reptile Diversity Patterns Under Climate and Land Use Change Scenarios in a Subtropical Montane Landscape in Mexico

ABSTRACTAimMountainous regions are rich in reptile biodiversity but face threats from climate and land use changes. Understanding how these factors affect reptile diversity in these regions can highlight key conservation hotspots that require effective conservation actions. Here, we explored reptile taxonomic and functional diversity patterns along the Sierra Madre del Sur region in southeast Mexico, and potential changes in future years caused by different climate and land use change scenarios.LocationSierra Madre del Sur, México.TaxonReptiles.MethodsWe used species distribution models and information on species traits to estimate taxonomic and functional diversity throughout the Sierra Madre del Sur (SMS) region under current and future climate and land use change scenarios.ResultsGreater taxonomic and functional diversity was observed in both temperate and tropical forests. Taxonomic diversity was higher in more drier areas at high elevations while higher functional diversity was observed in wetter areas at intermediate‐to‐high elevations. Lower diversity for both dimensions was associated with anthropic land uses. In future scenarios, both dimensions of diversity are expected to increase in temperate forest in highlands of central Oaxaca and decrease in the southcentral portion of the SMS, particularly for the worst scenarios due to increased deforestation rates.Main ConclusionsHigher taxonomic diversity in more drier areas at high elevations could be due to historical and evolutionary factors, while higher functional diversity in wetter areas at intermediate‐to‐high elevations may be explained by a higher environmental heterogeneity in forests within these conditions. Larger diversity losses in the southcentral portion of the SMS are probably due to larger predicted deforestation rates in those areas. Our results are valuable not just for informing conservation actions, such as the creation of protected natural areas but also to understand the underlying processes behind the patterns of reptile diversity.

Adaptive superpixel segmentation and pigment identification of colored relics based on visible spectral images

This work explores the extraction of the spatial distribution and chemical composition information of pigments in colored relics through visible spectral images. An adaptive superpixel segmentation method is proposed to extract the spatial distribution information of pigments. Quadtree decomposition is applied to generate nonuniform initial seed points based on the image homogeneity. These seed points are used as the initial cluster centers in an extended simple linear iterative clustering (SLIC) algorithm for visible spectral images to create superpixels of varying sizes that reflect the homogeneity. Each superpixel is subsequently treated as an individual area in the colored relics, and a pigment identification method based on the visible spectral reflectance is proposed to identify the pigments in these areas. A standard reference database is constructed using samples that simulate the painting process of ancient wall paintings in the Mogao Grottoes. Geometric features, which are characterized by the linear combination of the normalized visible spectral reflectance, its slope and its curvature, are designed to represent the chemical composition of pigments. The geometric features of the superpixels are compared with those of the pigments in the database using the Euclidean distance to determine the pigments in each area of the colored relics. This work is expected to provide scientific guidance for pigment selection in the color restoration of colored relics.

A New Dawn for Protist Biogeography

ABSTRACTAimBiogeographers have believed for a long time that the geographical distributions of protists are only determined by environmental conditions, because dispersal is not limited. During the past two decades, the field has come a long way to show that historical and spatial factors also significantly contribute to shaping protist distributions, calling for a reappraisal of our understanding of protist biogeography.MethodsWe review the current state‐of‐the‐art on the field of protist biogeography, highlighting several outstanding questions and opportunities. Our review brings together insights from different disciplines, ranging from morphology‐based research to environmental, population and speciation genomics.ResultsProtist communities harbour cosmopolitan and geographically restricted species and are shaped by both local environmental conditions and historical processes, yet the relative contributions of these patterns and processes likely differs depending on the geographic scale, protist lineage and the habitat that is being investigated. The field is ready to move beyond the decades‐long ubiquity versus (moderate) endemicity discourse and to instead ask why and where specific protist species and clades are more prone to widespread or restricted distributions. With the advent of next‐generation sequencing technologies, from whole‐genome sequencing to environmental and ancient DNA surveys, it is now possible to integrate insights from multiple lines of evidence and investigate protist communities, species and populations at an unprecedented scale and detail.OutlookTo further advance the field, the protist community needs to focus on understudied habitats and protist lineages, study the impact of protist traits on biogeographical patterns, perform targeted field and experimental work to disentangle the processes that underlie protist biogeographies and expand and develop databases with sequence, trait, distributional and phylogenetic information of protists. Given that a good understanding of species boundaries is central to unravelling protist biogeography, it remains crucial to invest in polyphasic taxonomic research.

Extraction of agricultural plastic greenhouses based on a U-Net Convolutional Neural Network Coupled with edge expansion and loss function improvement

ABSTRACT Agricultural plastic greenhouses (APGs) are crucial for sustainable agricultural planting, and accurate spatial distribution information acquisition is crucial. Deep learning network models can extract target features from remote sensing images more effectively than traditional interpretation methods, which face challenges like high workloads and poor repeatability. In this study, we aim to enhance the inventorying of Agricultural Plastic Greenhouses (APGs) by improving the extraction accuracy of their locations and numbers through remote sensing techniques. Utilizing GF-7 satellite imagery, we propose an enhanced U-Net convolutional neural network (CNN) model that incorporates edge information expansion and a joint loss function to optimize performance. The primary objective is to provide a rapid and accurate method for mapping APGs, which is crucial for effective agricultural management and environmental monitoring. The U-Net network’s accuracy was enhanced by 1.1% after expanding 3 × 3sample edge information, and further by 1.9% by combining edge extension and loss function constraints. Our results demonstrate that the modified U-Net model significantly improves extraction accuracy compared to traditional methods, thereby facilitating better inventory management and planning for agricultural cash crops. This advancement not only supports farmers in optimizing resources but also contributes to sustainable agricultural practices by enabling precise monitoring of APG distribution. Implication Statement Compared to traditional interpretation methods, which suffer problems such as heavy workloads, small adaptation ranges and poor repeatability, deep learning network models can better extract target features from remote sensing images. In this study, we used GF-7 image data to improve the traditional U-Net convolutional neural network (CNN) model. The Canny operator and Gaussian kernel (GK) function were used for sample edge expansion, and the binary cross-entropy and GK functions were used to jointly constrain the loss. Finally, APGs were accurately extracted and compared to those obtained with the original model. The results indicated that the APG extraction accuracy of the U-Net network was improved through the expansion of sample edge information and adoption of joint loss function constraints.

A Method for Quantifying Global Network Topology Based on a Mathematical Model

To facilitate a direct comparison of the differences in network resources among countries worldwide, this paper proposes a method for quantifying the relationship between autonomous systems and territorial networks from the perspective of network topology. Using global router-level network topology data as the foundational data for the network resources of various countries, we abstract the dual mapping information of router geographic distribution and operational ownership into a matrix-form mathematical model. By employing relevant indicators from both network scale and border connectivity, we compare matrix model data from different periods to quantitatively assess changes in the network structures of countries globally. The study results show that internet resources are concentrated in the United States, which owns 38.04% of the global routers, distributed across 87.88% of the countries, significantly impacting the global network. Compared to the average quantitative indicators of each country, 67.00% of the countries exhibit higher deployment consistency, 37.30% show higher border connection consistency, 23.81% perform prominently in terms of impact, and 46.20% have outstanding border node degrees. From a continental perspective, the analysis indicates that Asian and African countries have a closer relationship between AS and territorial networks, while Europe’s connections are relatively sparse. Over time, we observe a slight decline in deployment consistency in Asia, Africa, and Europe, a slight increase in border connection consistency in Asia, Africa, and North America, and enhanced impact in Asia, Africa, Europe, and South America. These trends suggest that the integration between AS and territorial networks is intensifying in most countries.

Numerical investigation on the core thermal hydraulic behavior of pool-type sodium-cooled fast reactor (SFR)

A thorough understanding of the reactor core thermal hydraulic behavior is essential for the design and safety analysis of Sodium-cooled Fast Reactors (SFR). Due to the application of hexagonal subassembly, the core thermal hydraulic behavior is significantly affected by the flow field within the subassemblies, the inter-wrapper region and the hot pool. Analysis of the core thermal hydraulic behavior requires a model coupling the three regions mentioned above, which has been identified as one of the thermal hydraulic challenges in SFR. In the present study, a 3D model that covers the three regions was developed for the core of the China Experimental Fast Reactor (CEFR) with the Computational Fluid Dynamic (CFD) code, Fluent. The inter-wrapper region and the hot pool were modeled in detail, while the subassemblies were modeled with a special porous medium model. The core thermal hydraulics behavior under steady state was studied, more specifically, information for the flow field distribution at the core outlet, the inter-wrapper flow and the duct wall temperature distribution was obtained. Under steady state, liquid sodium in the inter-wrapper region is supplied by the inner region of the hot pool. And it enters the inter-wrapper region from the core outer region and returns back to the hot pool inner region from the core central region. The inter-wrapper flow is cooled by non-fuel subassemblies and heated up by fuel subassemblies. For non-fuel subassembly, the ratio of the total heat transfer rate between the inter-wrapper flow and the subassemblies to the heat generated within subassemblies could reaches 96%; for fuel subassemblies, the maximum ratio of the total heat transfer rate between the inter-wrapper flow and the subassemblies to the heat generated within subassemblies is 2.45%. Significant temperature gradients have been observed on the duct wall, with maximum values of 156.69 K/m in the vertical direction and 2,196.00 K/m in the circumferential direction. The largest temperature gradient appears on the duct of subassemblies adjacent to the transition region of fuel subassemblies and non-fuel subassemblies.

New Documented Records of the Mesopelagic Fish Valenciennellus tripunctulatus (Sternoptychidae) in the Strait of Messina and a Review of Its Mediterranean Occurrences

The constellation fish, Valenciennellus tripunctulatus, is a small mesopelagic teleost typically found in equatorial and temperate waters worldwide, although the species has been also rarely recorded in the Mediterranean Sea (less than 20 specimens from the available literature since 1918). The Mediterranean records have been documented for the Strait of Messina, the southern Tyrrhenian Sea, the Ligurian Sea and the Adriatic Sea. The present paper offers an updated review on the occurrence of V. tripunctulatus in the Mediterranean basin and provides data on three new specimens, collected in the Strait of Messina between April 2010 and March 2024. Furthermore, we also report information from two individuals found in March 1992 and February 2017, respectively. Overall, the standard length of these specimens ranged from 24.1 to 28.2 mm, whereas weight varied from 0.18 g to 0.20 g. Morphometric and meristic data were reported, and this analysis revealed few differences between examined individuals in the number of PV (ventral series anterior to pelvic fin base) and AC (from anal fin origin to caudal fin base) photophore series. The relationship between total length and standard length (SL = 0.75 × TL + 2.98), total length and head length (HL = 0.17 × TL + 1.47) and standard length and head length (HL = 0.23 × SL + 0.88) showed high correlation values. Considering the lack of data on this species in the Mediterranean, updating morphometric, meristic, biological, ecological and distribution information is very important for taxonomic purposes and useful in understanding the characteristics of the regional population and eventual differences between Mediterranean stock(s) and those from other oceanic areas.

A Knowledge Distillation Method Based on Evidence Theory to Prevent Catastrophic Forgetting

Abstract Incremental learning is an emerging machine-learning approach designed to prevent catastrophic forgetting while learning a new task with knowledge retained from previous tasks. However, existing methods often must fully utilize the distributional information of the old task model’s outputs. To alleviate this, we propose a class incremental learning method grounded in evidence theory to leverage the distributional information of outputs from the old task model, which integrates uncertainty estimation into the knowledge distillation process to ensure the new task model effectively learns from the old task model’s distribution information. Specifically, we incorporate uncertainty estimation based on evidence theory to calculate knowledge distillation loss during training. We compute the uncertainty estimates of outputs from both the new and old task models, and then they are used in the knowledge distillation loss calculation. We propose a novel classification strategy that considers outputs’ probability and uncertainty estimates, which could determine the sample category without requiring an additional training phase or supplementary models. Experiments on the CIFAR-100 and ImageNet datasets demonstrate the effectiveness of the proposed method, showing that it outperforms existing methods by improving accuracy by 1%-2%. Results suggest that leveraging the distribution information of model outputs can effectively mitigate catastrophic forgetting in deep learning models within incremental learning scenarios.

Nanoparticle Tracking Analysis: An Effective Tool to Characterize Extracellular Vesicles

Extracellular vesicles (EVs) are membrane-enclosed particles that have attracted much attention for their potential in disease diagnosis and therapy. However, the clinical translation is limited by the dosing consistency due to their heterogeneity. Among various characterization techniques, nanoparticle tracking analysis (NTA) offers distinct benefits for EV characterization. In this review, we will discuss the NTA technique with a focus on factors affecting the results; then, we will review the two modes of the NTA techniques along with suitable applications in specific areas of EV studies. EVs are typically characterized by their size, size distribution, concentration, protein markers, and RNA cargos. The light-scattering mode of NTA offers accurate size, size distribution, and concentration information in solution, which is useful for comparing EV isolation methods, storage conditions, and EV secretion conditions. In contrast, fluorescent mode of NTA allows differentiating EV subgroups based on specific markers. The success of fluorescence NTA heavily relies on fluorescent tags (e.g., types of dyes and labeling methods). When EVs are labeled with disease-specific markers, fluorescence NTA offers an effective tool for disease detection in biological fluids, such as saliva, blood, and serum. Finally, we will discuss the limitations and future directions of the NTA technique in EV characterization.

Knowledge shortfalls on amphibian diets in Colombia: Future trends and challenges

AbstractAmphibians are increasingly threatened, leading to growing concern about their key role in natural ecosystems globally as predators and essential consumers in food webs. Effective conservation plans are linked to up‐to‐date distributional and ecological information, but dietary knowledge is often underrepresented. This information is essential for understanding ecological requirements, changes in the species and populations, impacts of habitat modification, and developing conservation strategies. Here, we present the current knowledge on amphibian diets in Colombia, to determine (a) the number of species studied and their distribution across families and genera; (b) the temporal and regional patterns in number of articles on amphibian diets; and (c) the trends in topics studied associated with amphibian diets; and to offer (d) a qualitative description of amphibian diets and the methods used for stomach contents collection. We found 70 published studies on the diet of Colombian amphibians between the years 1914 and 2022, including 100 species (11.6% of Colombian species). The Andean region is the best represented, and the Amazon and Orinoco the least. The topics most frequently studied were prey items consumed and ontogeny, followed by systematics and taxonomy, and land‐use change impacts. Forty‐one prey items were consumed, where Coleoptera and Hymenoptera were the most common prey items. While the development of information on amphibian diets has recently increased, knowledge remains limited, with a significant information gap for many Colombian species in different regions. Conducting studies in little‐explored areas of the country, especially the Amazon, Orinoco, and Pacific regions, should have high priority. Investigations should be focused on Caudata and Gymnophiona, plus the anurans of the Hemiphractidae and Pipidae families that do not have diet records in Colombia. Indeed, we evidence the necessity to perform trophic network analysis to understand better the energy flow between species and the associated spatial, temporal, or functional trait changes.

Synchrotron-aided exploration of REE recovery from coal fly ashes within a Canadian context

Coal ashes in Canada have gained attention as a potential source for recovering rare earth elements (REE) from industrial waste. However, the complex chemical properties of coal ashes have made it difficult to determine the desirability, feasibility, and viability of REE recovery. To address this issue, this study systematically investigated distribution and structural information, speciation and chemical-binding state, and purity and extraction capacity of REE in multiple Canadian coal ashes (i.e., 2 fly ash and 1 bottom ash samples) through synchrotron-based X-ray fluorescence mapping and adsorption spectrum analyses, as well as high-resolution REE sequential extraction quantitation. The results showed that Y, Ce, and La were present in the glass phase of the bottom ash, and the distributions of these REE elements correlated with Ca. The XANES analysis revealed that the dominant form of REE in coal fly ash (CFA) was REE oxides, indicating a transformation during combustion, while Y2O3 and Y2(CO3)3 were the predominant Y species identified in CFA. The study found that there is no correlation between P and REEs, suggesting that REEs in CFA may exist as discrete particles rather than being associated with amorphous glass. The extractability of REEs in bottom ash samples was lower than that in fly ash samples. Additionally, the benefits of REE recovery were estimated to be USD 99.82 to 215.21 per ton of fly ash through life cycle analysis, indicating that REE recovery from fly ashes is a promising path to supplement the REE supply chain in Canada.