Overlap In Distribution Research Articles

Investigating Hailstorm Updrafts and Nowcasting Hail Size Using a Novel Radar-Based Updraft Detection

Abstract Nowcasting hail size poses a major challenge in operational practice due to physical limitations of weather radar technology once hailstones are sufficiently large to enter the resonance scattering regime. Numerous radar-based hail size proxies have been derived in recent decades, but their performance is generally poor in identifying giant hail (≥10 cm). Using a novel thunderstorm updraft detection method, we examine the updraft characteristics of hailstorms in the U.S. Great Plains based on a NEXRAD dataset of 114 hail events between 2013 and 2023. We find that some radar-derived variables within the detected updraft are well suited for discriminating between small hail (1.0–3.0 cm) and severe hail (≥3.5 cm), e.g., minimum copolar cross-correlation coefficient in the midlevel updraft, whereas other radar metrics such as the area of reflectivity > 50 dBZ in the upper portion of the updraft suggest the presence of giant hail. However, the statistical distributions of each variable overlap for different hail sizes, and there is no single metric which performs well across the entire hail size spectrum. Therefore, we trained a random forest model to nowcast hail size categories using a multitude of these radar metrics. The model shows promising performance for discriminating hail sizes > 5 cm but requires further refinement for smaller hail. We showcase the model’s capabilities for a set of hailstorms in the Great Plains. Significance Statement Large hail, which may reach sizes up to 20 cm in extreme cases, is a severe threat in thunderstorms and responsible for significant damage in thunderstorm-prone areas around the world. Weather radars are generally used for issuing warnings for the threat of large hail, but it is surprisingly difficult to apply their data to distinguish between hail sizes. We utilize a new approach that detects the thunderstorm updraft region, which is where hailstones grow, and analyze the radar data therein. Based on these data, we then develop a model for assessing hail sizes that could be used for warnings and illustrate the model results for six hailstorms.

Species behavioral characteristics lead to unique fragmentation threats: The Nubian ibex as a case study

AbstractThe behavioral characteristics of species may result in certain populations being inherently more susceptible to fragmentation. For example, species exhibiting spatial sexual segregation or those constrained to elongated and narrow habitats. We studied the fragmentation threats, spatial dynamics, resource utilization, and movement ecology of a particularly vulnerable species that is both sexually segregated and constrained to elongated and narrow habitat—the north Judean Desert population of Nubian ibex (Capra nubiana). From 2016‒2020 we tracked 48 marked ibex (27 male, 21 female), of which 38 (20 male, 18 female) also had global position system (GPS) collars. Using GPS‐collar and camera‐trap data in zones delineated around perennial water sources (PWSs), we calculated ibex drinking frequencies and individual utilization distributions by season and sex, focusing on their overall (95% isopleth) and core (50% isopleth) home ranges. We quantified joint space use between sexes using a utilization distribution overlap index (UDOI) and ibex daily movements and space use via movement indices. Female groups formed philopatric activity centers that were anchored around PWSs year‐round and arranged in a metapopulation‐like structure, with no female movement detected between them. Conversely, movement of adult males changed seasonally, with the cores of male groups anchored around PWSs only during the dry season, and long‐range movement between female activity centers during the rut. Female groups also spent more time at steeper terrain and higher elevations compared with male groups. Outside the rut, groups of males and groups of females exhibited minimal joint space use (i.e., average dry season UDOI was 0.06). These patterns indicate high sensitivity of this population to intersexual fragmentation by obstacles (physical or virtual). Management strategies to mitigate fragmentation threats for such populations should be sex‐specific and landscape‐oriented.

Sperm as a speciation phenotype in promiscuous songbirds.

Sperm morphology varies considerably among species. Sperm traits may contribute to speciation if they diverge fast in allopatry and cause conspecific sperm precedence upon secondary contact. However, their role in driving prezygotic isolation has been poorly investigated. Here we test the hypothesis that, early in the speciation process, female promiscuity promotes a reduction in overlap in sperm length distributions among songbird populations. We assembled a data set of 20 pairs of populations with known sperm length distributions, a published estimate of divergence time, and an index of female promiscuity derived from extrapair paternity rates or relative testis size. We found that sperm length distributions diverged more rapidly in more promiscuous species. Faster divergence between sperm length distributions was caused by the lower variance in the trait in more promiscuous species, and not by faster divergence of the mean sperm lengths. The reduced variance is presumably due to stronger stabilizing selection on sperm length mediated by sperm competition. If divergent sperm length optima in allopatry causes conspecific sperm precedence in sympatry, which remains to be shown empirically, female promiscuity may promote prezygotic isolation and rapid speciation in songbirds.

Double localized surface plasmon‒enhanced-second-harmonic generation behavior of equilateral triangular aluminum nanoprisms

This paper presents second-harmonic generation (SHG) behaviors for different-sized equilateral triangular aluminum nanoprisms. These behaviors were observed under the double localized surface plasmon (LSP) resonance condition. The SHG conversion efficiency was substantially enhanced when the excitation and SHG wavelengths were simultaneously tuned to the LSP-resonance wavelengths. The fundamental and higher-order LSP modes could be used to enhance the SHG conversion efficiency. The nonlinear light‒matter interaction associated with the double LSP resonance was numerically analyzed while focusing on the spatial overlap of the near-field distributions between the excitation and SHG wavelengths. The double LSP resonance enhanced SHG behaviors have been realized by using several elegantly designed plasmonic metal nanostructures consisting of multi-elements. Our present study demonstrates this double LSP resonance enhanced SHG behavior from a single, simple-shape triangular aluminum nanoprism.

Clinical Impact of 3- versus 5-Minute Delay and 30- versus 60-Second Intervals on Unattended Automated Office Blood Pressure Measurements.

Guidelines advise automated office blood pressure (AOBP) with an initial 5-minute delay and multiple measurements at least 60 seconds apart. Recent studies suggest that AOBP may be accurate with shorter delays or intervals, but evidence in clinical settings is limited. Patients referred to one hypertension (HTN) center underwent 24-hour ambulatory blood pressure monitoring (ABPM) and one of four non-randomized, unattended AOBP protocols: a 3- or 5-minute delay with a 30 or 60-second interval, i.e., 3min/30sec/30sec, 3/60/60, 5/30/30 and 5/60/60 protocols. HTN was defined as systolic blood pressure ≥140 or diastolic blood pressure ≥90 mmHg. We compared differences in mean blood pressure and HTN classification between average AOBP and awake-time ABPM by t-tests and Fisher's exact test. Among 212 participants (mean 58.9 years, 61% women, 25% Black), there was substantial overlap in the probability distributions of awake-time ABPM and each of the three AOBP measures. Systolic blood pressure means were similar between the 5/60/60 and 3/30/30 protocols and 5/30/30 and 3/60/60 protocols. The 5/30/30 was associated with a higher proportion of systolic HTN, while the 3/60/60 protocol was associated with a higher proportion of diastolic HTN. There were no significant differences in systolic or diastolic HTN between 5/60/60 and 3/30/30 protocols with respect to awake-time ABPM. In this quality improvement study, the shortest AOBP protocol did not differ significantly from the longest protocol. The time savings of shorter protocols may improve AOBP adoption in clinical practice without meaningfully compromising accuracy.

Adaptive condition-aware high-dimensional decoupling remote sensing image object detection algorithm

Remote Sensing Image Object Detection (RSIOD) faces the challenges of multi-scale objects, dense overlap of objects and uneven data distribution in practical applications. In order to solve these problems, this paper proposes a YOLO-ACPHD RSIOD algorithm. The algorithm adopts Adaptive Condition Awareness Technology (ACAT), which can dynamically adjust the parameters of the convolution kernel, so as to adapt to the objects of different scales and positions. Compared with the traditional fixed convolution kernel, this dynamic adjustment can better adapt to the diversity of scale, direction and shape of the object, thus improving the accuracy and robustness of Object Detection (OD). In addition, a High-Dimensional Decoupling Technology (HDDT) is used to reduce the amount of calculation to 1/N by performing deep convolution on the input data and then performing spatial convolution on each channel. When dealing with large-scale Remote Sensing Image (RSI) data, this reduction in computation can significantly improve the efficiency of the algorithm and accelerate the speed of OD, so as to better adapt to the needs of practical application scenarios. Through the experimental verification of the RSOD RSI data set, the YOLO-ACPHD model in this paper shows very satisfactory performance. The F1 value reaches 0.99, the Precision value reaches 1, the Precision-Recall value reaches 0.994, the Recall value reaches 1, and the mAP value reaches 99.36%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document}, which indicates that the model shows the highest level in the accuracy and comprehensiveness of OD.

Hidden collective oscillations in a disordered mean-field spin model with non-reciprocal interactions

Abstract We study the effect of introducing separable quenched disorder on a non-equilibrium mean-field spin model exhibiting a phase transition to an oscillating state in the absence of disorder, due to non-reciprocal interactions. In the disordered model, the magnetisation and its time derivative no longer carry the signature of the phase transition to an oscillating state. However, thanks to the separable (Mattis-type) form of the disorder, the presence of oscillations can be revealed by introducing a specific, disorder-dependent observable. We also introduce generalised linear and non-linear susceptibilities associated either with the magnetisation or with its time derivative. While linear susceptibilities show no sign of a phase transition, the third-order susceptibilities present a clear signature of the onset of an oscillating phase. In addition, we show that the overlap distribution also provides evidence for the presence of oscillations, without explicit knowledge of the disorder.

Shallow water source depth discrimination based on a vertical linear array using deep learning

This study aims to explore source depth discrimination in shallow water waveguides using a vertical line array. Due to the similarity in physical characteristics of features and environmental parameters, the feature distributions of shallow and deep sources overlap in feature space. This overlap is further exacerbated by strong background noise, reducing detection reliability. Therefore, a deep learning-based source depth discrimination (DL-SDD) scheme is proposed. Specifically, this scheme is based on a residual structure, embedding channel attention mechanisms into the deep structure to eliminate noise-related information gradually. Furthermore, a specially designed loss function considers inter-class and intra-class distances to achieve compact and mutually distant distributions of source features. When this loss function is applied, the overlap of source feature distributions is suppressed in end-to-end feature learning, leading to a high detection probability. The numerical simulations demonstrate that the proposed DL-SDD outperforms traditional method, achieving a 7 % increase in detection probability and a 15 % decrease in false alarm rate, even near the discrimination depth. Furthermore, the discrimination depth is reduced by nearly half. Experimental results from the South China Sea validate the effectiveness of the proposed DL-SDD.

Inhibition of Botrytis cinerea infection on tomato leaves by submicronization of penthiopyrad particles

If the spray concentration of the pesticide remains constant, submicronization of the active ingredients significantly increase the particle number concentration, thereby substantially enhancing the probability of contact with plant pathogens and is anticipated to result in reduced pesticide usage. In this study, we investigated the effect of submicronization of pesticide active ingredients on the inhibitory effect against plant pathogens. Three types of monodispersed penthiopyrad (pesticide) particles with different median diameters and minimal overlap in the particle size distribution were successfully prepared using a poor solvent dilution method. Using these penthiopyrad particles, we conducted experiments on infection of tomatoes (model plants) with Botrytis cinerea (plant pathogen). The results showed that the submicronization of pesticide particles enhanced the inhibitory effects of the sprayed pesticide on the plant pathogen, while also decreasing the required amount of pesticide sprayed to the plants. Furthermore, confocal microscopy images showed that smaller particles are taken up by B. cinerea hyphae better than larger particles. Additionally, the bacterial flora on the leaf surface was not affected by submicronized pesticide particles larger than 100 nm. These findings imply that submicronization of pesticide active ingredients increases the probability of reaching targeted plant pathogens on the leaf surface, ultimately resulting in an increase in their uptake by the plant pathogens (i.e., significantly improved delivery of pesticides).

Regulating Charge Transfer in Cyanine Dyes: A Universal Methodology for Enhancing Cancer Phototherapeutic Efficacy.

ConspectusDue to the advantages of spatiotemporal selectivity and inherent noninvasiveness, cancer phototherapy, which includes both photodynamic therapy (PDT) and photothermal therapy (PTT), has garnered significant attention in recent years as a promising cancer treatment. Despite the commendable progress in this field, persistent challenges remain. In PDT, limitations in dyes manifest as low intersystem crossing (ISC) efficiency and oxygen-dependent photoactivity, resulting in unsatisfactory performance, particularly under hypoxic conditions. Similarly, PTT encounters consistent insufficiencies in the photothermal conversion efficiency (PCE) of dyes. Additionally, the suboptimal phototherapeutic efficacy often exhibits a limited immune response. These factors collectively impose significant constraints on phototherapy in oncological applications, leading to limited tumor inhibition, tumor recurrence, and even metastasis.Unlike strategies that rely on external assistance with complicated systems, manipulating excited-state deactivation pathways in biocompatible dyes offers a universal way to systematically address these challenges. Our group has devoted considerable effort to achieving this goal. In this Account, we present and discuss our journey in optimizing excited-state energy-release pathways through regulating molecular charge transfer based on cyanine dyes, which are renowned for their exceptional photophysical properties and harmonious biocompatibility. The investigation begins with the introduction of amino groups in the meso position of a heptamethine cyanine dye, where the intramolecular charge transfer (ICT) effect causes a significant enlargement of the Stokes shift. Subsequently, ICT induced by introducing functional electron-deficient groups in cyanines is found to decrease the overlap of electron distribution or narrow the energy gaps of molecular frontier orbitals. Such modifications result in a reduction of the energy gaps between singlet and triplet states or an improvement in internal conversion, ultimately promoting phototherapy efficacy in both primary and distant tumors. Furthermore, with the intensification of the charge transfer effect aided by light, photoinduced intramolecular electron transfer occurs in some cyanines, leading to complete charge separation in the excited state. This process enhances the transition to the ground or triplet states, improving tumor phototherapy and inhibiting metastasis by increasing the PCE or the yield of reactive oxygen species, respectively. Shifting focus from intramolecular to intermolecular interactions, we successfully constructed and explored cyanines based on intermolecular charge transfer. These dyes, with excited-state dynamics mimicking natural photosynthesis, generate radicals and facilitate oxygen-independent hypoxic tumor PDT. Finally, we outlined the existing challenges and future directions for optimizing phototherapeutic efficacy by regulating molecular charge transfer. This Account provides molecular-level insights into improving phototherapeutic performance, offering valuable perspectives, and inspiring the development of functional dyes in other application fields.

Formation mechanism of deep to ultra-deep carbonate reservoir: a case study of the Ediacaran Dengying Formation, Penglai area, Sichuan Basin

The formation of high-quality deep to ultra-deep carbonate reservoirs presents a topic worthy of thorough exploration. Focusing on the Ediacaran (Sinian) Dengying Formation in the Penglai area of the Sichuan Basin, we analysed genesis mechanisms of deep to ultra-deep marine carbonate reservoirs through drilling/logging, seismic data and analytical tests, which showed the dolomite reservoir primarily consists of secondary solution pores and cavities, exhibiting characteristics of vertical overlap and horizontal continuous distribution. The microbial mound beach, which represents the main dominant facies type within the reservoir, can be categorised into three types: high-quality reservoir, medium-quality reservoir and poor reservoir. The reservoir has undergone five stages: syngenetic to quasi-syngenetic, shallow burial, supergene, burial and deep burial adjustment stages. It is postulated that the development of deep to ultra-deep carbonate reservoirs is governed by sedimentary facies, with the type and structure of carbonate influencing the development and evolution of reservoir pores. Multiphase diagenetic fluids further modify and enhanced the properties of the reservoirs. Deep and ultra-deep carbonate reservoirs exhibit strong heterogeneity, and high-quality reservoirs are characterised by multi-factor joint control and multi-stage composite genesis. The lithological and structural–lithological traps associated with them commonly cluster in large areas so effective identification of favourable sedimentary facies and reservoirs is crucial for predicting deep to ultra-deep carbonate reservoirs, characterising traps and improving the success rate of drilling.

Judd-Ofelt analysis of dimeric europium carboxylates with gradually changing distortions of the crystal field around Eu3+ ion

Experimental and theoretical Judd-Ofelt intensity parameters Ωλ, rates of radiative Arad and nonradiative Anrad processes, and quantum efficiency of luminescence were calculated for a series of related aromatic and aliphatic carboxylates [Eu2(RCOO)6L2] (L - 1,10-phenanthroline or 2,2′-bipyridine) using the LUMPAC software. The behavior of these characteristics in the sequence of europium carboxylates with the gradually changing distortions of the crystal field, which is mainly caused by variation in the bond lengths of the bridging-cyclic COO− groups with Eu3+ ion, was analyzed. A correlation between the changes in the value of the Ω2 intensity parameter, the radiative rate Arad, and the ratio of metal-ligand bond lengths in the Eu coordination polyhedron was demonstrated. The dependence of the parameter Ω2 on the distribution of metal-ligand orbital overlap among Eu-ligand bonds of the compound was revealed. The higher Ω2 values in the set of aromatic carboxylates are associated with a more distorted nearest environment of the Eu3+ ion which is caused by the influence of the bulky R fragments. It is shown that the intensity of f-f transitions of the Eu3+ ion in the compounds under investigation is determined foremost by the dynamic coupling (DC) mechanism. The contribution of this mechanism to the parameters Ω2 and Ω4 is close to 100 %, its contribution to the Ω6 parameter is 85–92 %. The luminescence quantum efficiency for the studied europium carboxylates varies in the range of 52–74 %.

Suitable Habitat Distribution and Niche Overlap of the Sable (Martes zibellina) and Yellow-Throated Marten (Martes flavigula) in Taipinggou National Nature Reserve, Heilongjiang Province, China.

The global focus on fostering harmonious interactions and promoting rational coexistence among wildlife species to uphold or reinstate biodiversity remains a prominent area of interest. We conducted a study on the sable and yellow-throated marten in Taipinggou National Nature Reserve, Heilongjiang, China, using the line transect method and infrared camera traps from 2022 to 2023. We then analyzed the overlap of their suitable habitats and niches with the aim of gaining insight into the interspecific competition between these two species. We found that the suitable habitat areas for the sable and yellow-throated marten were 55.20 km2 and 23.28 km2, accounting for 24.86% and 10.48% of the total area of this study, respectively. The overlap between the suitable habitats for the sable and yellow-throated marten was 15.73 km2, accounting for 28.5% and 67.6% of their suitable habitat, supporting our Hypothesis 1. The first principal component (Dim1) of the niche explained 35.4% of the overall variability, which is mainly related to the environmental variables "Distance from Settlements" and "Distance from Roads". Overall, 25.5% of the total variability was explained by the second principal component (Dim2), associated with "Slope" and "Distance from Coniferous and Broadleaved Mixed Forest". The niches occupied by the sable and yellow-throated marten were both off-center of the environmental background space, with the niches of the sable being larger than those of the yellow-throated marten. Schoener's D index was 0.56, indicating a high degree of niche overlap between the sable and yellow-throated marten, supporting our Hypothesis 2. Our study is helpful in terms of formulating conservation and management policies for the sable and yellow-throated marten.

Parameter Optimization Method in Multidimensional Umbrella Sampling.

Umbrella sampling (US) is an effective method for calculating free-energy landscapes (FELs). However, the complexity of controlling the sampling positions complicates multidimensional FEL calculations. In this study, we proposed a method for controlling sampling by optimizing the US parameters. This method comprises the introduction of a target point and the optimization of the parameters to sample a window around this point. We approximated each window to normal distributions using an umbrella integration method and calculated the divergences between the window distributions and the state distributed at the target position by a variationally enhanced sampling method. Thus, the minimization of the divergence facilitated sampling around the target point, after which the parameters could be optimized on the fly while performing equilibration simulation. In practice, our method employs bias potentials with off-diagonal terms, ensuring a more efficient calculation of multidimensional FEL. Additionally, we developed an algorithm for determining the target point for automated FEL search; the algorithm samples in a specified direction while controlling the overlap of distributions. We performed three different FEL calculations as examples: (1) the calculation of the permeation of a water molecule through a lipid bilayer (one-dimensional FEL), (2) the calculation of the internal structural changes in alanine dipeptide in water (two-dimensional FEL), and (3) the calculation of the internal structural changes from a β-strand structure to an α-helix structure in alanine decapeptide (Ala10, 16-dimensional FEL). These results confirmed that our method could control the number of US windows and calculate the high-dimensional FELs that could not be evaluated by the conventional US method.

A Ranking-Based Cross-Entropy Loss for Early Classification of Time Series.

Early classification tasks aim to classify time series before observing full data. It is critical in time-sensitive applications such as early sepsis diagnosis in the intensive care unit (ICU). Early diagnosis can provide more opportunities for doctors to rescue lives. However, there are two conflicting goals in the early classification task-accuracy and earliness. Most existing methods try to find a balance between them by weighing one goal against the other. But we argue that a powerful early classifier should always make highly accurate predictions at any moment. The main obstacle is that the key features suitable for classification are not obvious in the early stage, resulting in the excessive overlap of time series distributions in different time stages. The indistinguishable distributions make it difficult for classifiers to recognize. To solve this problem, this article proposes a novel ranking-based cross-entropy () loss to jointly learn the feature of classes and the order of earliness from time series data. In this way, can help classifier to generate probability distributions of time series in different stages with more distinguishable boundary. Thus, the classification accuracy at each time step is finally improved. Besides, for the applicability of the method, we also accelerate the training process by focusing the learning process on high-ranking samples. Experiments on three real-world datasets show that our method can perform classification more accurately than all baselines at all moments.

Do DOM quality and origin affect the uptake and accumulation of a lipid-soluble contaminant in a filter feeding ascidian species (Ciona) that can target small particle size classes?

The widely reported increase of terrestrial dissolved organic matter (terrDOM) in northern latitude coastal areas (“coastal darkening”) can impact contaminant dynamics in affected systems. One potential impact is based on differences in chemical adsorption processes of the molecularly larger terrDOM compared to marine DOM (marDOM) that leads to increased emulsification of lipophilic contaminants with terrDOM. Filter feeders filter large amounts of water and DOM daily and thus are directly exposed to associated contaminants through both respiration and feeding activity. Thus, increased exposure to terrDOM could potentially lead to an increase in bioaccumulation of lipid soluble contaminants in filter feeders. To assess the effect of DOM on bioaccumulation in filter feeders, we exposed the mucous based filter feeding ascidian Ciona intestinalis (formerly known as Ciona intestinalis Type B), to the lipophilic veterinary drug teflubenzuron (log KOW: 5.39) in combination with four DOM treatments: TerrDOM, marDOM, a mix of the two called mixDOM, and seawater without DOM addition. The exposure lasted for 15 days, after which the individuals in all DOM treatments showed a trend towards higher bioaccumulation of Teflubenzuron than those in the seawater control. However, there was considerable overlap in posterior distributions. Against our expectations, marDOM resulted in the highest bioaccumulation factor (BAF), followed by mixDOM, with terrDOM resulting in the lowest BAF except for seawater (kinetic BAF L/kg median, 2.5 %–97.5 % percentile marDOM 94, 74–118; mixDOM 82, 63–104; terrDOM 79; 61-99; seawater 61, 44–79). All BAFs were below the level of concern according to the EU REACH regulation (BAF < 2000 L / kg) and, therefore, likely not environmentally problematic in the examined context. However, the results show that DOM can act as a dietary vector; thus, different combinations of contaminants, DOM, and filter feeding organisms should be tested further.

Habitat use by a bird community in a Caatinga area: habitat seasonality and overlap

Habitat degradation is one of the main drivers of biodiversity loss, a phenomenon that significantly manifests in the Caatinga domain, where extensive habitat areas undergo modifications. Therefore, understanding how organisms select their habitats becomes crucial for effective conservation management. In this context, the present study aims to analyze habitat use, seasonality, and overlap within a bird community in an area located within the Caatinga domain, specifically at Fazenda Aba. Twelve monthly expeditions were conducted using the point-count method to estimate usage areas, habitat intensity, and overlap during both dry and rainy periods. Usage areas were measured using the Minimum Convex Polygon (MCP 100%) method, while the Kernel 95% estimator was employed to assess habitat intensity. Overlap was calculated using the Utilization Distribution Overlap Index (UDOI). The results revealed comprehensive use of the study area by the bird community, with more pronounced usage intensity in riparian forest environments. Additionally, an increase in usage areas was observed during the rainy period compared to the dry season, reflecting greater overlap during the scarcity season. It is suggested that riparian forest habitats play a fundamental role in maintaining avifauna, especially during droughts, promoting seasonal movements of species that tend to shift to areas with higher resource availability, resulting in convergence of utilized areas.

Sparse-to-Dense Point Cloud Registration Based on Rotation-Invariant Features

Point cloud registration is a critical problem because it is the basis of many 3D vision tasks. With the popularity of deep learning, many scholars have focused on leveraging deep neural networks to address the point cloud registration problem. However, many of these methods are still sensitive to partial overlap and differences in density distribution. For this reason, herein, we propose a method based on rotation-invariant features and using a sparse-to-dense matching strategy for robust point cloud registration. Firstly, we encode raw points as superpoints with a network combining KPConv and FPN, and their associated features are extracted. Then point pair features of these superpoints are computed and embedded into the transformer to learn the hybrid features, which makes the approach invariant to rigid transformation. Subsequently, a sparse-to-dense matching strategy is designed to address the registration problem. The correspondences of superpoints are obtained via sparse matching and then propagated to local dense points and, further, to global dense points, the byproduct of which is a series of transformation parameters. Finally, the enhanced features based on spatial consistency are repeatedly fed into the sparse-to-dense matching module to rebuild reliable correspondence, and the optimal transformation parameter is re-estimated for final alignment. Our experiments show that, with the proposed method, the inlier ratio and registration recall are effectively improved, and the performance is better than that of other point cloud registration methods on 3DMatch and ModelNet40.

No evidence for niche competition in the extinction of the South American saber-tooth species

The end of South American isolation during the Great American Biotic Interchange (GABI) promoted the contact between South and North American saber-tooth forms that evolved in isolation. This contact may have driven saber-tooth species to a competitive interaction, resulting in the extinction of the South American saber-tooth form. Here, we used paleoclimatic data to compare the climatic niche of the saber-tooth forms Thylacosmilus atrox (from South America), Smilodon fatalis, and Smilodon populator (both originally from North America). We evaluated niche width, overlap, and similarity to infer potential geographic distribution overlap and competition between these North and South American predators. To do so, we obtained the climatic variables from sites where occurrence fossil records were available. Our results suggest that T. atrox had a narrower climatic niche compared to Smilodon species. Although we found a significant climatic niche overlap and similarity between S. fatalis and T. atrox, it seems unlikely that both species have co-occurred. Low niche overlap and similarity between T. atrox and S. populator dismiss competitive interaction between them. Moreover, climatic niche and low tolerance for environmental changes may have been the cause of the South American saber-tooth extinction.

Open-source code maps traumas for targeting interventions: Applying the model to compare penetrating traumas with “Stop the Bleed” training locations

BackgroundTo improve equitable access to geospatial analysis, a free open-source R package, called Rosymap, was created to map trauma incident locations. MethodsTo demonstrate the R package, penetrating trauma events for all patients who received care at a level one trauma center, and the locations of all “Stop the Bleed” training locations between 2019 and 2022 were geospatially analyzed. ResultsThe level one trauma center treated 1531 patients for penetrating traumas between 2019 and 2022. Using Rosymap, a map was produced showing the poor overlap in distribution between penetrating traumas and “Stop the Bleed” training locations. ConclusionRosymap, a free open-source GIS R package, visualized that the majority of “Stop the Bleed” training locations were not performed within clusters of penetrating traumas serviced by our level one trauma center. These results suggest that trauma providers and public health advocates should consider geospatial analysis when planning interventions and when attempting to choose locations equitably and accurately. To facilitate and promote the implementation of geospatial analysis, Rosymap is available as open-source code.