Changes In Distribution Research Articles

Construction of a numerical model for cigarette smoking and combustion and simulation of combustion cone shape

Abstract Understanding the thermal conditions inside a burning cigarette is a top priority for controlling chemical emissions and cigarette design. Since experimental methods are difficult to observe in depth, this paper starts from the perspective of numerical simulation and models the structure of the tobacco distribution of the cigarette, integrating the end surface ignition model, puffing model, chemical reaction model, heat and mass transfer and diffusion model have established a three-dimensional comprehensive model that can represent the changes in combustion cone morphology during cigarette combustion. The model covers chemical reaction and mass transfer as well as generation, flow and reaction mechanism. The simulation results show that the model can better predict the temperature distribution, component distribution and combustion cone morphology changes during cigarette smoking and combustion. It provides an effective means for in-depth research on cigarette combustion.

Assessing Alterations of Rainfall Variability Under Climate Change in Zengwen Reservoir Watershed, Southern Taiwan

This study aims to detect changes in rainfall variability caused by climate change for various scenarios in the CMIP6 (Coupled Model Intercomparison Project Phase 6) multi-model ensemble. Projected changes in rainfall unevenness in terms of different timescale indices using three categories, namely WD50 (number of wettest days for half annual rainfall), SI (seasonality index), and DWR (ratio of dry-season to wet-season rainfall) are analyzed in Zengwen Reservoir watershed, southern Taiwan over near future (2021–2040) and midterm future (2041–2060) relative to the baseline period (1995–2014) under SSP2-4.5 and SSP5-8.5 scenarios. The projected rainfall for both baseline and future periods is derived from 25 GCMs (global climate models). The results indicate that noticeably deteriorated rainfall unevenness is projected in the Zengwen Reservoir watershed over future periods, which include decreased WD50, increased SI, and decreased DWR. Though there were noticeable differences in the rainfall projections by the different GCMs, the overall consensus reveals that uncertainties in future rainfall should not be ignored. In addition, WD50 has the greatest deviated relative change in mean, which implies that the short-timescale rainfall unevenness index is easily affected by climate change in the study area. Distributional changes in rainfall unevenness determined by simultaneously considering alterations in relative changes in mean and standard deviation indicated that there was no single dominant category. However, the top two categories, with summed frequencies exceeding 0.5, characterize different properties of rainfall unevenness indices. The top two categories of WD50 and SI commonly have decreased mean and increased mean, respectively, but nearly equal frequencies of the top two categories in DWR exhibit opposite variations. The proposed rainfall unevenness change detection approach provides a better understanding of the impacts of climate change on rainfall unevenness, which is useful for preparing adaptive mitigation measures for coping with disasters induced by climate change.

Changes in waterbird occurrence and abundance at their northern range boundaries in response to climate warming: importance of site area and protection status

AbstractClimate warming is driving changes in species distribution, but habitat characteristics can interact with warming temperatures to affect populations in unexpected ways. We investigated wintering waterbird responses to climate warming depending on habitat characteristics, with a focus on the northern boundary of their non‐breeding distributions where winter climatic conditions are more extreme. At these Nordic latitudes, climate warming is expected to drive positive changes in species occurrence and abundance, with likely differences in species‐specific responses. We analyzed the occurrence and abundance of 18 species of waterbirds monitored over 2,982 surveys at 245 inland wetlands over a 25‐year period in Sweden. We used hierarchical modeling of species communities (HMSC) which enabled us to relate species‐specific changes to both functional traits and phylogenetic relatedness. We investigated occurrence and abundance changes in response to average temperature, temperature anomalies, site area, site protection status (Natura 2000), and land use in agricultural and urban surfaces. Unsurprisingly, both average temperatures and temperature anomalies were the most important variables influencing positively waterbird occurrence and abundance. For 60% of the species, the effect of temperature anomalies was even stronger in large or protected wetlands. Geese and mallard occurred more often at sites surrounded by agricultural and urban surfaces, respectively, but their occurrence in these habitats was not affected by interactive effects with climate warming. Species abundance was greater inside protected areas only for 11% of the species, but occurrence probability was higher inside protected areas for 44% of the species. Overall, we observed that species thermal affinity was a strong predictor for positive species response to temperature anomalies, and that species sharing similar phylogenetic history had similar relationships with environmental variables. Protection of large wetlands and restoration of the surrounding habitats are two targets for climate change adaptation strategies to facilitate future responses of waterbirds to climate warming.

Inhibitory effect of 1,4,5,6-tetrahydroxy-7,8-diprenylxanthone against NSCLC with L858R/T790M/C797S mutant EGFR

Epidermal growth factor receptor (EGFR)-activating mutations are critical factors in the development of EGFR-driven non-small-cell lung cancer (NSCLC), and molecular targeted therapies have focused on inhibiting these mutations. EGFR tyrosine kinase inhibitors (TKIs) have remarkable inhibitory effects on NSCLC with EGFR mutations. However, acquired resistance limits the clinical application of EGFR-TKIs, highlighting the need for discovery of novel therapeutic strategies. 1,4,5,6-tetrahydroxy-7,8-diprenylxanthone is a natural product derived from Garcinia xanthochymus, has shown potential anti-tumor activity, but the underlying mechanism needs further elucidation. In this study, we developed Ba/F3 and NIH/3T3 cells harboring EGFR L858R/T790M/C797S mutation, and then found that 1,4,5,6-tetrahydroxy-7,8-diprenylxanthone exerted inhibitory effects against cells with EGFR L858R/T790M/C797S mutation. Additionally, 1,4,5,6-tetrahydroxy-7,8-diprenylxanthone exhibited potent anti-tumor activity against cells harboring the triple-mutant EGFR by promoting apoptosis and inducing changes in cell cycle distribution. Furthermore, 1,4,5,6-tetrahydroxy-7,8-diprenylxanthone was found to significantly reduce tumor growth via suppressing the phosphorylation of EGFR in tumor tissues. These effects are associated with binding of 1,4,5,6-tetrahydroxy-7,8-diprenylxanthone to EGFR resulting in the suppression of extracellular signal-regulated kinase (Erk) phosphorylation. In conclusion, our results suggest that 1,4,5,6-tetrahydroxy-7,8-diprenylxanthone may be a potential novel candidate for further investigation and treatment of NSCLC with the triple-mutant EGFR.

Influence of Electrolyte Saturation on the Performance of Li-O2 Batteries.

Electrolyte saturation can strongly affect the Li-O2 battery performance. However, it is unclear to what extent saturation reduction will impact the battery capacity. In this study, we investigated the influence of electrolyte saturation and distribution within a porous positive electrode on the deep discharge-charge capacities and cycling stability. The study used both models and experiments to investigate the change of electrolyte distribution, double-layer capacitance, ohmic resistance, and O2 concentration in the positive electrode at different electrolyte saturations. Results revealed that electrodes with 60% electrolyte saturation achieved almost the same maximum discharge (6.38 vs 6.76 mAh/cm2) and charge (5.52 vs 5.65 mAh/cm2) capacities with fully saturated electrodes. The partially wet positive electrode (40% saturation) obtained more cycles than the electrode with 100% saturation before the discharge capacity dropped below the cutoff point. However, the electrode with 40% saturation had a low average charging efficiency of 88.76%, whereas the fully saturated electrode obtained 98.96% charging efficiency. Moreover, the fully wet positive electrode had the lowest overpotential during cycling (1.26-1.39 V). The measured electrochemically active surface areas showed that even 40% saturation could sufficiently wet the positive electrode surface and obtain a double-layer capacitance (18.12 mF) similar to that with 100% saturation (20.4 mF). Furthermore, a considerable increase in O2 concentration at wetted surface areas was observed for the electrolyte saturation of less than 60% due to the significantly higher O2 diffusivity in the gas phase.

Ab Initio Structure and Dynamics of Beryllium Monofluoride and Its Anion.

The accurate potential energy functions of beryllium monofluoride, BeF, and its anion, BeF-, have been determined from ab initio calculations using the coupled-cluster approach, up to the CCSDTQP level of approximation, in conjunction with the augmented correlation-consistent core-valence basis sets, aug-cc-pCVnZ, up to septuple-zeta quality. The vibration-rotation energy levels of the two species were predicted to near the "spectroscopic" accuracy. Changes in the electron density distribution upon formation of the Be-F chemical bond are discussed.

Long-Term Changes in Composition and Distribution of Bumblebees in Urban Areas

Abstract The distribution of bumblebee species in Wrocław (SW Poland) was studied based on data from ten UTM grid squares between 1879 and 2018, and the composition and abundance of bumblebee species between 2011 and 2018. The results were compared with historical data available for the last 139 years, including published materials and collections of the Museum of Natural History (University of Wrocław). Twenty-six bumblebee species,including six species of cuckoo bumblebees of the subgenus Psithyrus, were recorded. One species was not confirmed during the later period, nine were strongly decreasing both in the range of distribution, seven other were expanding significantly in Wrocław and three were new in the Wrocław city boundaries. Negative and positive tendencies resulted from both anthropogenic and natural factors. All bumblebees that appeared in the city of Wrocław and increased their abundance were species that prefered forest and shrub areas, while species that disappeared from the city and decreased in numbers were species who prefered open areas.

Fully coupled thermal-structural-vibration characteristics of 3-axis machine tools with complex hybrid linear axis-spindle systems considering structural nonlinearities

For machine tools composed of functional components bonded by joints with structural nonlinearities, the load- and temperature-dependent nonlinear restoring force,stiffness, and frictional heat generationfrom the jointdetermine its complex dynamic fully coupled thermal-structural-vibration characteristics. In response, in this work, considering the vibration feedback dominated by the structural vibration and employing a partition-based closed-loop iterative algorithm, a fully coupled thermal-structural-vibration model that characterizes the nonlinear coupling between temperature and mechanical fields is developed with the joint as the link. The multi-body dynamics model of the whole machine tool, considering the flexibility of the screw shaft, spindle, and joint nonlinearity, characterizes the milling dynamics influenced by structural vibration and regeneration effects. The global thermal resistance network model with dynamic heat flux, viscosity-temperature effect, and time-varying thermal resistanceis establishedto characterize the thermal characteristics. The partition-based closed-loop iterative algorithm is employed to realize the multi-field coupling and consider the moving heat source and the load distribution change caused by the reciprocating moving joint. Considering the changes in contact angle and contact deformation caused by preload, dynamic load, and thermal effect, load- and temperature-dependent nonlinear joint restoring force and stiffnessare developed. Based on the viscosity-temperature effects and the change of contact friction caused by thermal expansion and dynamic load, the load- and temperature-dependent nonlinear joint frictional heat generation is calculated. The milling load from tool-workpiece interaction is calculated, and the influence of multi-field coupling on regenerative chatter is explored. The proposed model was experimentally verified, andthe effectof parameterswas numerically investigated. The results show that the dynamic milling load excites the whole machine tool vibration, and for every 10 μm increase in cutting depth, the radial amplitude of the tool nose increased by at least 1 μm. The nonlinear coupling between temperature and mechanical field significantly affects the system response, and the joint contact stiffness dominates the multi-field coupling behavior.

Dysregulation of R-loop homeostasis shapes the immunosuppressive microenvironment and induces malignant progression in melanoma.

Dysregulated R-loop homeostasis leads to DNA replication stress and genomic instability, a major driver of cancer. However, the role of R-loops in melanoma development remains unclear. We established an R-loop scoring model based on a single-cell RNA sequencing dataset and evaluated the association between the R-loop score with the melanoma immune microenvironment and treatment response. We explored the role of CENPA-mediated changes in R-loop distribution during melanoma progression by DNA/RNA immunoprecipitation and sequencing and a series of functional experiments. We found that malignant cells with high R-loop scores may be involved in melanoma progression by modulating immune evasion, metabolic reprogramming, and cancer-related pathways. A cell communication analysis revealed that high-score R-loops play an important role in altering cell-cell interactions and limiting the CD8 + cytotoxic T cell response and T cell accumulation. CENPA silencing induced changes in R-loop distribution, upregulated Hippo signaling activity, and inhibited tumor cell proliferation and migration. Moreover, the R-loop score can predict the prognosis and immunotherapy effect of melanoma patients. Our work reveals the potential molecular mechanism by which abnormal R-loops promote melanoma progression, which may help develop anticancer therapies based on R-loops or R-loop regulators.

Genomics-Informed Range Predictions Under Global Warming Reveal Reduced Adaptive Diversity Whilst Buffering Range Shifts for a Marine Snail.

Understanding the genetic basis of local adaptation in thermal performance is useful for predicting species distribution shifts under anthropogenic climate change. Many species are distributed across multiple biogeographic regions, and the uniquely adapted populations in each region may respond to future ocean warming with distinct distribution changes. In the present study, we investigated phylogeographic patterns, thermal sensitivity, and genetic differentiation in the intertidal snail Littorina brevicula along China's coast. Whole-genome sequencing results based on a newly assembled chromosome-level genome revealed two genetic lineages, with a north-south divergence that is linked to the thermal environment. Within each lineage, individuals could be further subdivided into genetic subgroups that differ at key genomic loci underpinning differences in upper heat tolerance. Heat stress drives adaptive divergence across multiple levels of organization, from the individual to the biogeographic level. Taking into account genetic diversity associated with variation in heat tolerance, a physiological species distribution model (pSDM) was applied to predict the distributions of the different genetic subgroups in response to climate change. Both northern and southern lineages were predicted to experience declines in habitat suitability under a 4°C future warming scenario, and that a genotypic subset of snails from the southern lineage may even be driven to extinction. These findings illustrate that even when a species' range is maintained, it can nonetheless experience a significant decrease in adaptive diversity as a result of climate change. The integrated approach presented here, which considered both physiological and adaptive genetic variation at the level of individuals within a biogeographical context, provided new insights into how marine species can respond to global warming.

Pharmacological Treatment of Obesity in Older Adults.

Obesity is a complex health issue with growing prevalence worldwide. It is also becoming more prevalent in the population of older adults (i.e., 65 years of age and older), affecting frequency and severity as well as other comorbidities, quality of life and consequently, life expectancy. In this article we review currently available data on pharmacotherapy of obesity in the population of older adults and its role in obesity management. Even though there is growing evidence, in particular in the general population, of favourable efficacy and safety profiles of glucagon-like peptide-1 (GLP-1) receptor agonists liraglutide and semaglutide, and recently dual GLP-1 and glucose-dependent insulinotropic polypeptide (GIP) agonist tirzepatide, concise guidelines for older adults are not available to this day. We further discuss specific approaches to frequently represented phenotype of obesity in older adults, in particular sarcopenic obesity and rationale when to treat and how. In older adults with obesity there is a need for more drug trials focusing not only on weight loss, but also on geriatric endpoints including muscle mass preservation, bone quality and favourable fat distribution changes to get enough data for evidence-based recommendation on obesity treatment in this growing sub-population.

Study on aerodynamic breakup of non-Newtonian liquid droplets and the distribution characteristics of their sub-droplets

In industrial applications, the secondary breakup of droplets and the size distribution of their sub-droplets are crucial for atomization performance indicators. In this work, a high-speed digital camera is utilized to experimentally and theoretically study the secondary breakup process of xanthan gum (XG) droplets and the size distribution changes of resulting sub-droplets in continuous airflow by changing the Weber number and effective Ohnesorge number. In addition, a detailed study is conducted on the liquid ring with the highest liquid content. The results show that at low Weber numbers, the number of nodes generated at the XG droplet ring is the same as that of the water droplet, following “the combined R-T/aerodynamic drag” mechanism. However, the final diameter of the nodes differs significantly from that of the water droplet. The particle size of XG liquid ring nodes is not only affected by the Weber number but also decreases with the increase of the effective Ohnesorge number. The particle size of the remaining broken sub-droplets in the liquid ring decreases with the increase of the effective Ohnesorge number. Finally, the spatial range of droplet breakup under different parameters is described by using the liquid ring breakup angle, and it is found that the breakup angle of the liquid ring is mainly related to the breakup mode.

Near-Term Forecasting of Terrestrial Mobile Species Distributions for Adaptive Management Under Extreme Weather Events.

Across the globe, mobile species are key components of ecosystems. Migratory birds and nomadic antelope can have considerable conservation, economic or societal value, while irruptive insects can be major pests and threaten food security. Extreme weather events, which are increasing in frequency and intensity under ongoing climate change, are driving rapid and unforeseen shifts in mobile species distributions. This challenges their management, potentially leading to population declines, or exacerbating the adverse impacts of pests. Near-term, within-year forecasting may have the potential to anticipate mobile species distribution changes during extreme weather events, thus informing adaptive management strategies. Here, for the first time, we assess the robustness of near-term forecasting of the distribution of a terrestrial species under extreme weather. For this, we generated near-term (2 weeks to 7 months ahead) distribution forecasts for a crop pest that is a threat to food security in southern Africa, the red-billed quelea Quelea quelea. To assess performance, we generated hindcasts of the species distribution across 13 years (2004-2016) that encompassed two major droughts. We show that, using dynamic species distribution models (D-SDMs), environmental suitability for quelea can be accurately forecast with seasonal lead times (up to 7 months ahead), at high resolution, and across a large spatial scale, including in extreme drought conditions. D-SDM predictive accuracy and near-term hindcast reliability were primarily driven by the availability of training data rather than overarching weather conditions. We discuss how a forecasting system could be used to inform adaptive management of mobile species and mitigate impacts of extreme weather, including by anticipating sites and times for transient management and proactively mobilising resources for prepared responses. Our results suggest that such techniques could be widely applied to inform more resilient, adaptive management of mobile species worldwide.

Enhanced microwave absorption using multiple heterostructures derived from in-situ grown Sn-metal-organic framework on La-doped Fe3O4

As a representative magnetic oxide absorber, Fe3O4 has attracted considerable research attention owing to its remarkable magnetic saturation strength as well as semiconducting properties. Doping Fe3O4 with La3+ leads to 3d-4f magnetic coupling and ion distribution changes due to the unique electron configuration and large ionic radius of La3+, thereby greatly enhancing the magnetic performance. However, high density, low dielectric loss, and low permeability at high frequencies inhibit the electromagnetic wave absorption (EMWA) performance of ferrites. In this study, stick-shaped Sn metal-organic framework (MOF) is in-situ grown on La3+-doped Fe3O4 using a surfactant. After high-temperature annealing, the SnO2/porous carbon composites derived from Sn-MOF wrap the ferrite, forming a core-shell heterostructure, which not only prevents oxidation but also enhances the EMWA performance. Among the prepared LaxFe3-xO4/SnO2/C (LFSC) samples, LFSC-2 (with LaxFe3-xO4 to Sn-MOF ratio of 1:2) exhibits strong absorption performance with a minimum reflection loss (RLmin) of −44.1 dB. Furthermore, the gradient metamaterial based on LFSC-3 shows ultra-broadband EMWA with an effective absorption bandwidth (RLmin ≤ −10 dB) of 13.17 GHz. In addition, the LFSC-2 sample demonstrates excellent radar stealth capability in the radar cross section (RCS) far-field response, achieving an RCS reduction value of 20.4 dB·m2.

Reconstructing MODIS normalized difference snow index product on Greenland ice sheet using spatiotemporal extreme gradient boosting model

The spatiotemporally continuous data of normalized difference snow index (NDSI) are key to understanding the mechanisms of snow occurrence and development as well as the patterns of snow distribution changes. However, the presence of clouds, particularly prevalent in polar regions such as the Greenland Ice Sheet (GrIS), introduces a significant number of missing pixels in the MODIS NDSI daily data. To address this issue, this study proposes the utilization of a spatiotemporal extreme gradient boosting (STXGBoost) model generate a comprehensive NDSI dataset. In the proposed model, various input variables are carefully selected, encompassing terrain features, geometry-related parameters, and surface property variables. Moreover, the model incorporates spatiotemporal variation information, enhancing its capacity for reconstructing the NDSI dataset. Verification results demonstrate the efficacy of the STXGBoost model, with a coefficient of determination of 0.962, root mean square error of 0.030, mean absolute error of 0.011, and negligible bias (0.0001). Furthermore, simulation comparisons involving missing data and cross-validation with Landsat NDSI data illustrate the model’s capability to accurately reconstruct the spatial distribution of NDSI data. Notably, the proposed model surpasses the performance of traditional machine learning models, showcasing superior NDSI predictive capabilities. This study highlights the potential of leveraging auxiliary data to reconstruct NDSI in GrIS, with implications for broader applications in other regions. The findings offer valuable insights for the reconstruction of NDSI remote sensing data, contributing to the further understanding of spatiotemporal dynamics in snow-covered regions.

Great Gerbils (Rhombomys opimus) in Central Asia Are Spreading to Higher Latitudes and Altitudes.

The great gerbil (Rhombomys opimus) is a gregarious rodent in Central Asia and is one of the major pests found in desert forest and grassland areas. The distribution changes and migration routes of R. opimus in Central Asia under climate change remain unexplored. This study employed multi-model ensemble, correlation analysis, jackknife method, and minimum cumulative resistance (MCR) model to simulate the potential habitat of R. opimus under current and future (2030 and 2050) climate scenarios and estimate its possible migration routes. The results indicate that the ensemble model integrating Random Forest (RF), Gradient Boosting Machine (GBM), and Maximum Entropy Model (MaxEnt) performed best within the present climate context. The model predicted the potential distribution of R. opimus in Central Asia with an area under the curve (AUC) of 0.986 and a True Skill Statistic (TSS) of 0.899, demonstrating excellent statistical accuracy and spatial performance. Under future climate scenarios, northern Xinjiang and southeastern Kazakhstan will remain the core areas of R. opimus distribution. However, the optimal habitat region will expand relative to the current one. This expansion will increase with the rising CO2 emission levels and over time, potentially enlarging the suitable area by up to 39.49 × 104 km2. In terms of spatial distribution, the suitable habitat for R. opimus is shifting toward higher latitudes and elevations. For specific migration routes, R. opimus tends to favor paths through farmland and grassland. This study can provide guidance for managing and controlling R. opimus under future climate change scenarios.

Heavy metal exposure reduces larval gut microbiota diversity of the rice striped stem borer, Chilo suppressalis.

Cadmium (Cd), a widely distributed environmental pollutant in agroecosystems, causes negative effects on crops and herbivores through bottom-up processes. The gut microbial community of an insect can play a critical role in response to metal stress. To understand how microbiota affect the stress responses of organisms to heavy metals in agroecosystems, we initially used 16S rRNA sequencing to characterize the larval gut microbiota of Chilo suppressalis, an important agricultural pest, exposed to a diet containing Cd. The species richness, diversity, and composition of the gut microbial community was then analyzed. Results revealed that while the richness (Chao1 and ACE) of gut microbiota in larvae exposed to Cd was not significantly affected, diversity (Shannon and Simpson) was reduced due to changes in species distribution and relative abundance. Overall, the most abundant genus was Enterococcus, while the abundance of the genera Micrococcaceae and Faecalibaculum in the control significantly superior to that in Cd-exposed pests. Phylogenetic investigation of microbial communities by the reconstruction of unobserved states (PICRUSt) showed that the intestinal microorganisms appear to participate in 34 pathways, especially those used in environmental information processing and the metabolism of the organism. This study suggests that the gut microbiota of C. suppressalis are significantly impacted by Cd exposure and highlights the importance of the gut microbiome in host stress responses and negative effects of Cd pollution in agroecosystems.

Preliminary investigation of the effects of high-temperature thermal activation on the activity of graphite tailings and the mechanical properties of graphite tailings mortar

The disposal of graphite tailings, a byproduct of graphite mining, poses significant recycling challenges. This study explores eco-friendly cement mortar by partially replacing sand with activated graphite tailings, focusing on waste utilization. Activating the pozzolanic properties of graphite tailings at various thermal activation temperatures converts them into high-quality binder materials. Quantitative assessments of graphite tailings' activity, conducted through ion leaching tests and raw material diffraction analysis, produce an activity index Ka, evaluating their performance under different thermal activation temperatures. Variable testing of substitution rates and activation temperatures examines changes in mechanical properties, microstructure, and pore distribution of the graphite tailings mortar. Optimum results reveal a 30 % substitution rate and a 750°C activation temperature. Graphite tailings, as pozzolanic binder materials, enhance mortar strength by improving particle size distribution, reducing "micro-area bleeding" and "boundary effects". After thermal activation, reactive minerals on the tailings' surface undergo secondary hydration reactions with cementitious products, modifying chemical structures and micro-morphology at the interface. Semi-quantitative XRD analysis and FT-IR spectroscopy characterize the ensuing chemical reactions, unveiling molecular bond and functional group changes. The superior performance of thermally activated graphite tailings primarily stems from increased active SiO2 and Al2O3 post-activation. The active SiO2 and Al2O3 reacts with cementitious products to form C-(A)-S-H gels, filling micro-pores at the tailings-mortar interface, which is the key characteristic that enables graphite tailings to serve as high-quality pozzolanic binder aggregates. A predictive model for compressive strength, utilizing reference models from solid waste mortar concrete, quantifies the positive impact of chemical activation. The theoretical results obtained from this predictive model closely align with the experimental findings.

Rapid Evolution of Host Repertoire and Geographic Range in a Young and Diverse Genus of Montane Butterflies.

Evolutionary changes in geographic distribution and larval host plants may promote the rapid diversification of montane insects, but this scenario has been rarely investigated. We studied rapid radiation of the butterfly genus Colias, which has diversified in mountain ecosystems in Eurasia, Africa, and the Americas. Based on a dataset of 150 nuclear protein-coding genetic loci and mitochondrial genomes, we constructed a time-calibrated phylogenetic tree of Colias species with broad taxon sampling. We then inferred their ancestral geographic ranges, historical diversification rates, and the evolution of host use. We found that the most recent common ancestor of Colias was likely geographically widespread and originated ~3.5 Ma. The group subsequently diversified in different regions across the world, often in tandem with geographic expansion events. No aspect of elevation was found to have a direct effect on diversification. The genus underwent a burst of diversification soon after the divergence of the Neotropical lineage, followed by an exponential decline in diversification rate toward the present. The ancestral host repertoire included the legume genera Astragalus and Trifolium but later expanded to include a wide range of Fabaceae genera and plants in more distantly related families, punctuated with periods of host range expansion and contraction. We suggest that the widespread distribution of the ancestor of all extant Colias lineages set the stage for diversification by isolation of populations that locally adapted to the various different environments they encountered, including different host plants. In this scenario, elevation is not the main driver but might have accelerated diversification by isolating populations.

MGFNet: Cross-scene Crowd Counting via Multistage Gated Fusion Network

Existing crowd counting methods are mainly trained and tested in similar scenarios. When the testing and training scenarios of the model are different, the counting accuracy of these methods will sharply decrease, which seriously limits their practical application. To address this problem, we propose a multistage gated fusion network (MGFNet) for cross-scene crowd counting. MGFNet is primarily composed of dynamic gated convolution units (DGCU) and multilevel scale attention blocks (MSAB) modules. Specifically, DGCU uses a dynamic gating path to supplement detailed information to reduce the loss of crowd information and overestimation of background in different scenarios. MSAB calibrates crowd information at different scales and perspectives in different scenes by generating attention maps with discriminative information. In addition, we used a new global local consistency loss to optimize the model to adapt to changes in crowd density and distribution. Extensive experiments on four different types of scene counting benchmarks show that the proposed MGFNet achieves superior cross-scene counting performance.