Suitable Distribution Research Articles

National Park Double Boundary Delimitation: A Synergy-Based Approach Integrating Biodiversity and Ecosystem Services—An Example of Proposed Ailaoshan–Wuliangshan National Parks in China

The demarcation of national park boundaries is crucial for comprehensive planning, effective management, and maintaining the integrity of ecosystems and biodiversity. This research uses the proposed ‘Ailaoshan–Wuliangshan’ National Park (AWNP) in Yunnan Province, China, as the study area and adheres to the principles of systematic conservation planning (SCP). It employs the Marxan 2.43, MaxEnt 3.4.4, and InVEST 3.14.2 models to predict suitable distribution areas for key endangered species within the AWNP, identifies core ecological source areas, priority conservation areas, and conservation gaps, and constructs a double boundary protection framework. The study’s findings indicate that the potentially suitable habitats for the major rare and endangered species, as predicted by the MaxEnt model, are predominantly located in the Ailaoshan and Wuliangshan areas, with a smaller portion distributed in the Konglonghe area. The InVEST model assessment of habitat quality revealed that the total area of the core ecological source areas is 4775.26 km2, accounting for 35.34% of the total study area. The Marxan model identified a total area of 1064.22 km2 as priority conservation areas, constituting 7.90% of the total study area. Additionally, it revealed conservation gaps of 302.1 km2, which represent 2.20% of the total area. Ultimately, by integrating biodiversity conservation and ecosystem services, the boundaries of the AWNP were optimized into a double boundary delineation model: the inner boundary, characterized by rigid control, spans an area of 1076.20 km2, while the outer boundary, characterized by elastic management, covers an area of 3056.92 km2. Corresponding management recommendations are proposed for the different areas. The double boundary delineation method proposed in this study can, to a certain extent, reconcile the conflict between biodiversity conservation and resource utilization, providing an appropriate reference for the demarcation and dynamic management of national park boundaries in China.

Fitting Probability Distributions and Statistical Trend Analysis of Rainfall of Agro-climatic Zone of West Bengal

This research aimed to identify the most appropriate probability distribution for modeling average monthly rainfall in the agro-climatic zones of West Bengal and to detect any trends in this data. The study utilized historical rainfall data spanning 51 years (1970-2020) obtained from the IMD in Pune. To determine the best-fitting distribution and assess trends, 23 different probability distributions were employed, with the Mann-Kendall test and Sen’s slope estimator used for trend analysis. Goodness-of-fit tests, including the Kolmogorov-Smirnov, Anderson-Darling, and Chi-square tests, were employed to determine the most suitable distribution. The findings indicated that the Generalized Extreme Value, Gamma, and Lognormal (3-parameter) distributions were the best fits for two specific districts. The monthly rainfall distributions can be effectively used for predicting future monthly rainfall events in the region. The Mann-Kendall test revealed an increasing trend in rainfall for Kalimpong and Nadia Districts and a decreasing trend for Malda District.

Assessing the Suitability of Probability Distribution Models for Streamflow Analysis in Peninsular Malaysia

Streamflow analysis is indeed a need for Malaysia which always threaten by extreme streamflow events including flooding. However, the determination of the most suitable probability distribution for streamflow analysis has been the major concern and received considerable critical attention recently. The purpose of this study is to analyse the performances of several distributions in fitting the streamflow data collected form 11 streamflow stations in Peninsular Malaysia. and select the best performed distribution eventually. Normal, Generalized Extreme Value (GEV), three-parameter Gamma (G3), two-parameter Gamma (G2), three-parameter Weibull (W3), two-parameter Weibull (W2), three-parameter Log-Normal (LN3) and two-parameter Log-Normal (LN2) were used in this study to fit the maximum, minimum, and mean streamflow with monthly and seasonal time scales by using Easyfit software. The performances of distributions were evaluated through constructing Probability-Probability (P-P) Plot, Cumulative Distribution Function (CDF) and conducting goodness-of-fit tests including Chi-square () Test, Anderson-Darling (AD) Test and Kolmogorov-Smirnov (KS) Test. All the results were tabulated for comparison and the most suitable probability distribution was selected. Overall, the results indicated that the GEV distribution was the best fit distribution for most of the stations and most of the data series or time scales, while the LN3 distribution appeared to be the second-best distribution. These findings add to a growing body of literature on the selection of probability distribution especially for the streamflow analysis in Peninsular Malaysia. Besides, these findings provide significant information and practical knowledge in supporting the future development of streamflow-related plans or management including the flood and drought mitigation plans.

Models reveal shifting distribution of climatic suitability for pawpaw (Asimina triloba [L.] Dunal) cultivation under future climate change scenarios

The pawpaw (Asimina triloba [L.] Dunal) is a deciduous tree notable for its large edible fruit. Native to the eastern US and Canada, it has earned attention as a horticultural commodity and focus of scientific inquiry. However, few studies have modeled its potential future distribution under climate change. This study predicted the current and future potential distribution for pawpaw in North America and globally, with a focus on understanding future climatic suitability for fruit cultivation. This study first modeled suitability via the Maximum Entropy (MaxEnt) method by relating climate predictors with different datasets on pawpaw distribution, including nursery locations growing pawpaw. It also trained a boosted regression tree (BRT) model to estimate where sufficient heat accumulation for fruit ripening would occur. The models were applied to two future times (2041–2060 and 2081–2100), four emissions scenarios (SSP126, SSP245, SSP370, and SSP585), and climate projections from three climate models. Using nursery locations, the MaxEnt model yielded a mean area-under-the-curve statistic of 0.978 (standard deviation = 0.009) using 10-fold cross-validation, indicating strong predictive performance. The model suggested optimal conditions for pawpaw at these values: -4 °C for minimum temperature of coldest month, 26 °C for maximum temperature of warmest month, 88 cm for annual precipitation, and 0 % for precipitation seasonality. Models suggested shifting suitable climate conditions and accompanying increases in heat accumulation for fruit ripening. Northern America, Eastern Europe, and Northern Europe were predicted to have higher and increasing suitability; Western Europe, Southern Europe, and Eastern Asia were predicted to have higher but decreasing suitability. Little uncertainty existed due to collinearity shift or dissimilarity between current and future climate, but more uncertainty existed when predictions were based on differing climate model projections. This study provides insight into the pawpaw's potential response to climate change, and guidance on future locations for cultivation.

Analyzing AZ-non-Maxwellian distributions in Earth’s magnetosphere: MMS observations

A study of velocity distribution function in Earth’s magnetosphere is conducted using high-resolution measurements from the Magnetospheric Multiscale Spacecraft (MMS). The analysis focuses on the AZ-non-Maxwellian distribution that is a complex velocity-space structure, exhibiting a power-law distribution of moments. By imposing constraints on the spectral indices of the AZ-velocity distribution, the most suitable distribution for modeling Earth’s magnetosphere is determined. The combined use of MMS data and analysis of velocity distribution provides new insights into the behavior of plasma particles and the velocity space structures responsible for energy dissipation in plasmas. Understanding particle distribution, behavior, and the influence of cold ions in Earth’s magnetosphere is crucial for advancing our knowledge of plasma physics and has practical implications for space weather and magnetospheric dynamics. Addressing the remaining uncertainties and challenges in measurements, analysis of non-Maxwellian distribution of ions is essential for a comprehensive understanding of space plasma environments.

Duration Diabetes Survival Times Modelling Using Some Extended Lomax Distribution

The precise modeling of survival time in diabetes is essential for accurately estimating the potential lifespan of individuals diagnosed with diabetes. One of the key factors in assessing the potential survival times of diabetes patients in a specific region is the probability distribution of diabetes survival times. Therefore, data on diabetes survival times are necessary to conduct statistical modeling, particularly in determining the most suitable probability distribution. Statistical models are developed to draw conclusions about the probability distribution of diabetic patients at the Mandau Regional General Hospital (RSUD) in Bengkalis Regency, Riau Province. To achieve this, six distributions will be utilized and evaluated to identify the best model for describing diabetes survival times. The primary objective of this research is to identify the most appropriate distribution to represent the survival times of diabetes patients from 50 individuals in the Bengkalis region, using the Lomax (LM) distribution, three parameters modified Lomax distributions (Rayleigh Lomax (RL), Logistics Lomax (LL), New Rayleigh Lomax (NRL)) and four parameters modified Lomax Distribution (Odd Lomax Log Logistics (OL), Novel Extended Power Lomax (PL)). The maximum likelihood method will be employed to estimate the parameter values of the distributions used in this study. Additionally, graphical assessments (density-density plot) and numerical criteria (Akaike’s Information Criterion (AIC), -log likelihood (-l)) will be utilized to determine the best-fitting model. In most instances, the results obtained from graphical assessments were consistent but differed from the numerical criteria. The model with the lowest values of AIC and -l was selected as the best fit. Overall, the RL and OL distributions was identified as the most suitable model.

Projecting the Potential Global Distribution of Sweetgum Inscriber, Acanthotomicus suncei (Coleoptera: Curculionidae: Scolytinae) Concerning the Host Liquidambar styraciflua Under Climate Change Scenarios.

Acanthotomicus suncei is a newly discovered bark beetle in China that significantly threatens the American sweetgum Liquidambar styraciflua. In recent years, this pest has spread from its original habitat to many surrounding cities, causing substantial economic and ecological losses. Considering the wide global distribution of its host, Liquidambar styraciflua, this pest is likely to continue to spread and expand. Once the pest colonizes a new climatically suitable area, the consequences could be severe. Therefore, we employed the CLIMEX and Random Forests model to predict the potential suitable distribution of A. suncei globally. The results showed that A. suncei was mainly distributed in Southern China, in South Hokkaido in Japan, Southern USA, the La Plata Plain in South America, southeastern Australia, and the northern Mediterranean; these areas are located in subtropical monsoon, monsoonal humid climates, or Mediterranean climate zones. Seasonal rainfall, especially in winter, is a key environmental factor that affects the suitable distribution of A. suncei. Under future climates, the total suitable area of A. suncei is projected to decrease to a certain extent. However, changes in its original habitat require serious attention. We found that A. suncei exhibited a spreading trend in Southwest, Central, and Northeast China. Suitable areas in some countries in Southeast and South Asia bordering China are also expected to show an increased distribution. The outward spread of this pest via sea transportation cannot be ignored. Hence, quarantine efforts should be concentrated in high-suitability regions determined in this study to protect against the occurrence of hosts that may contain A. suncei, thereby avoiding its long-distance spread. Long-term sentinel surveillance and control measures should be carried out as soon as A. suncei is detected, especially in regions with high suitability. Thus, our findings establish a theoretical foundation for quarantine and control measures targeting A. suncei.

Projected expansion in two influenza-susceptible birds' distribution under climate and land-cover changes on the Qinghai-Tibetan Plateau

Avian influenza is a global zoonotic disease influencing bird conservation and public health. Climate and land-cover changes can significantly impact influenza-susceptible species' distribution, thereby influencing avian influenza outbreaks. The Qinghai-Tibetan Plateau (QTP) plays a crucial role in avian influenza virus transmission and is susceptible to environmental changes. Here, we focused on two influenza-susceptible birds, the bar-headed goose (Anser indicus) and brown-headed gull (Chroicocephalus brunnicephalus), to predict their distribution on the QTP under climate and land-cover change scenarios. We integrated satellite tracking, field surveys, and publicly available datasets to collect species occurrence. Then, we utilized Biomod models to predict bird distribution under current and future scenarios. Our results indicated that the distance to water bodies (DW) and the mean temperature of the wettest quarter (BIO 8) significantly influenced the distribution of bar-headed geese and brown-headed gulls. The highly suitable distributions of both species are concentrated in the northeastern QTP and the Changtang Plateau, with only the Qaidam Basin showing a decrease in the future. Their future distribution has roughly doubled, with expansions toward western and higher elevations. We highlighted the influence of climate and land cover changes on bird distribution, and identified key areas of bird distribution, which are also critical areas for future avian influenza monitoring and prevention.

Priority Conservation Area of Quercus mongolica Under Climate Change: Application of an Ensemble Modeling

As the primary secondary tree species in Northeast China, Quercus mongolica possesses significant ecological and economic value. This study employed the Biomod2 platform in conjunction with ArcGIS spatial analysis to assess the potential suitable habitat distribution area of Q. mongolica under current climatic conditions. Furthermore, it forecasted the distribution range and niche changes of potentially suitable habitats for Q. mongolica from 2022 to 2090 and pinpointed the key environmental factors influencing its distribution. The findings reveal that the total potential suitable area for Q. mongolica covers 74,994.792 km2, predominantly spread across Inner Mongolia, Heilongjiang, Jilin, and other regions. The primary determinants of suitable area distribution were peak temperature of hottest month, lowest temperature of coldest month, and altitude. Under future climate scenarios, the potentially suitable habitats of Q. mongolica are anticipated to diminish to varying extents, with the distribution center exhibiting a tendency towards northward migration. Concurrently, the overlap among different climate scenarios is predicted to expand over time. This investigation facilitates a comprehensive understanding of Q. mongolica’s adaptation to climate change, enabling informed adjustments and serving as a valuable reference for the preservation and sustainable management of Q. mongolica populations.

Predicting Potential Distribution of Teinopalpus aureus Integrated Multiple Factors and Its Threatened Status Assessment.

The accurate prediction of the niche and the potential distribution of a species is a fundamental and key content for biodiversity related research in ecology and biogeography, especially for protected species. Biotic interactions have a significant impact on species distribution but are often overlooked by SDMs. Therefore, it is crucial to incorporate biotic interaction factors into SDMs to improve their predictive performance. The Teinopalpus aureus Mell, 1923 is endemic to high altitudes in southern East Asia, renowned for its exceptional beauty and rarity. Despite the significant conservation value, its spatial distribution remains unclear. This study integrated climate data, host plants, and empirical expert maps to predict its potential distribution. The results indicated that utilizing the species richness of host plants as a surrogate for biotic interactions was a simple and effective way to significantly improve the predictive performance of the SDMs. The current suitable distribution of T. aureus and its host plants is highly fragmented, primarily concentrated in the Nanling and Wuyi Mountains, and consisting of numerous isolated small populations. Given climate change, their distribution is significantly shrinking, increasing the threatened level in the future. Especially for the population of T. aureus hainani Lee, the likelihood of extinction is extremely high. Abiotic factors not only directly affect the distribution of T. aureus but also indirectly impact it through the host plants. This was evident in the delayed response of T. aureus to climate change compared to its host plants, which is called the "hysteresis effect" caused by biotic interactions. Overall, we tentatively suggest regarding T. aureus as a vulnerable species. In the future, multiple measures could be taken to indirectly protect the feeding and habitat resources of T. aureus by conserving host plants, thereby enhancing its survival prospects.

Seasonal spatial distribution of groundwater suitability in the Cabo Frio shallow coastal aquifer, Rio de Janeiro, Brazil: applying groundwater quality index and GIS approaches

Seasonal spatial distribution of groundwater suitability in the Cabo Frio shallow coastal aquifer, Rio de Janeiro, Brazil: applying groundwater quality index and GIS approaches

Spatial Distribution Pattern of Aromia bungii Within China and Its Potential Distribution Under Climate Change and Human Activity.

Aromia bungii is a pest that interferes with the health of forests and hinders the development of the fruit tree industry, and its spread is influenced by changes in abiotic factors and human activities. Therefore, exploring their spatial distribution patterns and potential distribution areas under such conditions is crucial for maintaining forest ecosystem security. This study analyzed the spatial differentiation characteristics of the geographic distribution pattern of A. bungii in China using Moran's I and the Getis-Ord General G index. Hot spot distribution areas were identified using Getis-Ord Gi*. An optimized MaxEnt model was used to predict the potential distribution areas of A. bungii within China under four shared economic pathways by combining multivariate environmental data: (1) prediction of natural environmental variables predicted under current climate models; (2) prediction of natural environmental variables + human activities under current climate models; and (3) prediction of natural environmental variables under the future climate models (2050s and 2070s). Meanwhile, MigClim was used to simulate the unoccupied suitable area in the presence of obstacles under future climate change. The results showed that human activities, minimum temperature of the coldest month, and precipitation of the wettest month had positive effects on the distribution of A. bungii. However, in the current period, human activities drastically reduced the survival area of A. bungii, and its suitable distribution area was mainly concentrated in the eastern and central regions of China. Under the influence of climate change in the future, the habitat of A. bungii will gradually increase. Additionally, the MigClim model indicates that the area unoccupied by A. bungii has been on a continuous increasing trend. This study provides a positive reference for the prevention and control of A. bungii and the maintenance of forest health and ecosystem security, and provides important theoretical guidance for researchers, policymakers, and governments.

PREDICTING THE POTENTIAL DISTRIBUTION OF Pinus cernua L.K. PHAN EX AVER., K.S. NGUYEN AND T.H. NGUYEN, A CRITICALLY ENDANGERED CONIFER SPECIES

Pinus cernua L.K. Phan ex Aver., K.S. Nguyen and T.H. Nguyen (Pinaceae) is a critically endangered species restricted to the Laos - Vietnam border. The population of this species has been declining due to habitat loss and forest fire. Predicting the potential distribution of the species is an important priority for conservation plans and strategies. In this study, a MaxEnt model was used for predicting the potential distribution of P. cernua using 21 occurrence data and 13 environmental variables. Precipitation of driest month (with 32.3% of contribution), annual mean diurnal range (23.4%), elevation (18.4%), and aspect (12.3%) are crucial factors for predicting the species’ potential distribution in the MaxEnt model, while remaining factors are less important factors. The suitable distribution was predicted in the north-western region of Vietnam and the adjacent regions of Son La and Thanh Hoa provinces (Vietnam) and Houaphan province (Laos) with 1,544 km2 in total. The high, medium, and low suitability areas are 159 km2 (10%), 475 km2 (31%), and 910 km2 (59%), respectively. The current protected areas do not contain many of the possible habitats for this species. Priority should be given to conservation efforts for species in these potentially suitable locations both in- and outside of current protected areas, particularly in the surrounding area of Vietnam and Laos.

Predicting the habitat suitability and species richness of plants of Great Himalayan National Park under different climate change scenarios.

This study elucidates the distribution of plants in Great Himalayan National Park (GHNP), India, in current and different future climate change scenarios. The distribution of plants and habitat suitability in GHNP due to climate change was analyzed by MaxEnt, species distribution model (SDM) algorithm. In this study, species presence records were retrieved through field survey and published literature. We have projected the distribution of 44 plant species using MaxEnt and tested whether GHNP is performing well in conserving the plant species. Initially, we have constructed a model for each species and created the habitat suitability map from average of ascii files and later we added the maps of all species in order to make binary map to show the species richness in the selected climate scenarios. The model was created using the HADGEM-2 global circulation model in 2050 and 2070years by using climate change situations of RCP 2.6 and RCP 8.5. The area under curve (AUC) values in the final models of 44 plant species were in the range 0.70-0.97 that indicates statistically significant results. The model identified precipitation of driest month followed by altitude and annual mean temperature as most determining variables in the distribution of plants of GHNP in selected climate scenarios. In the present study, we found that overall suitable habitat increased for nine species, decreased for thirty-four, and unchanged for one plant species in terms of percent area change from current to future scenarios. So these nine species were found to be more adaptable towards changing climate than the other plant species in this study. The species richness was high in western and southwestern parts of GHNP in the current scenario, however under future climatic scenarios, species richness shows a decreasing trend. Based on our findings, it can be concluded that GHNP should be prioritized for conserving the plant species.

Development of a method for evaluating fabric surface contamination by particulate matter using fluorescent particles

Functional clothing products are being developed to prevent the attachment of particulate matter (PM). However, currently, PM-blocking performance of such products cannot be quantitatively evaluated. This study developed a method for measuring fabric surface contamination by PM by contaminating textile fabrics with PM and using an image processing technique. Silicate particles exhibiting fluorescence characteristics with a suitable size distribution were selected as PM simulants. The fabric surface contamination was calculated by contaminating textile fabrics under wind speed and PM concentration conditions similar to actual atmospheric environment. The number of pixels was obtained in the black and white binary images converted from the images of the textile fabrics captured under an ultraviolet (UV) light source. Experiments were performed using finished nylon fabric with PM-blocking performance and raw nylon fabric without PM-blocking performance. Comparison of the fabric surface contamination shows that it is possible to evaluate the PM-blocking performance of fabrics.

Enhancing hydraulic efficiency in jet impingement sprinklers: Comparative analysis of aperture ratios compared with non-impingement sprinklers

A jet impingement sprinkler was designed based on asymmetric collision between the primary and secondary jets to replace traditional rotating sprinklers that require additional water distribution devices to provide suitable water distribution at low pressures. The study focuses on the ratio of apertures between primary and secondary nozzles, deriving a theoretical relationship based on jet momentum. The factors contributing to the variation in hydraulic performance between jet-impingement and non-impinging sprinklers are elucidated by combining hydraulic performance experiments with experiments using high-speed photography (HSP). The results show that the developed jet impingement sprinkler achieved a smoother water distribution trend. The wetted radius and Christiansen's uniformity coefficient of the jet impingement sprinkler were evaluated using the Criteria Importance via the Intercriteria Correlation (CRITIC) method. A comparison of the average scores shows that an aperture ratio of 1.66 performs best under full pressure. By contrast, an aperture ratio of 1.33 exhibited superior performance at low pressure. Jet deflection angle and jet breakup length were obtained through HSP experiments. The relative error between the measured and theoretical jet deflection angles was less than 5%, demonstrating the reliability of the proposed theoretical calculation method. A non-linear curve was used to establish the relationship among the aperture ratio, diameter of the primary nozzle exit, jet breakup length, average measured jet deflection angle, working pressure, and wetted radius. The relative error between the calculated and measured values was within 4%, indicating the suitability of the new formula for calculating the wetted radius of jet impingement sprinklers.

Potential Global Distribution and Habitat Shift of Prunus subg. Amygdalus Under Current and Future Climate Change

The genus of Prunus subg. Amygdalus are endangered Tertiary-relict plants that are an essential source of woody plant oil. In order to provide a theoretical basis for better protection and utilization of species in the Prunus subg. Amygdalus. This study collected global distribution information for six species within the Prunus subg. Amygdalus, along with data on 29 environmental and climatic factors. The Maximum Entropy (MaxEnt) model was used to simulate the globally suitable distribution areas for these species within the subgenus. The suitable results showed that the area under the test curve (AUC) values of the simulation results were more than 0.8, indicating that the simulation results have high accuracy. Temperature, precipitation, UV-B, and altitude were critical environmental factors affecting the distribution of each species in Prunus subg. Amygdalus. Currently, the distribution area of six species in this genus, from largest to smallest, is Prunus triloba (Lindl.) Ricker, Prunus tenella Batsch, Prunus amygdalus Batsch, Prunus pedunculata Maxim, Prunus mongolica Maxim and Prunus tangutica (Batal.) Korsh. The simulation results of distribution areas showed that under the ssp2.45 and ssp5.85 scenarios, the potential distribution areas of P. amygdalus, P. tangutica, and P. pedunculata all show a decreasing trend, while the distribution areas of P. mongolica and P. tenella, and P. triloba exhibit an increasing trend. The general distribution of P. amygdalus, P. mongolica, and P. tenella will trend to transfer in a northwest direction. P. tangutica and P. pedunculata were affected by other environmental factors (such as slope, altitude, and soil pH), and the distribution area has a tendency to move northeastward. The P. triloba moved to the southwest. The spatiotemporal distribution patterns of Prunus subg. Amygdalus can be used as a reference for forest management and to formulate species conservation strategies.

Prediction of Potential Suitable Distribution Areas for Northeastern China Salamander (Hynobius leechii) in Northeastern China.

The Northeastern China Salamander (Hynobius leechii) is classified as a rare, nationally protected Class II wild animal in China. Its population is declining, and its habitat is deteriorating. This study aimed to predict the distribution of suitable habitats for the Northeastern China Salamander under both current and future climate scenarios, utilizing the MaxEnt model optimized through ENMeval parameters. Species distribution data were collected from field surveys, existing literature, amphibian records in China, and the Global Biodiversity Information Network. A total of 97 records were compiled, with duplicate records within the ENMTools grid unit removed, ensuring that only one record existed within every 5 km. Ultimately, 58 distinct distribution points for the Northeastern China Salamander were identified. The R software package 'ENMeval 2.0' was employed to optimize the feature complexity (FC) and regularization multiplier (RM), and the optimized model was applied to assess the suitable distribution regions for the Northeastern China Salamander under present and future climate conditions. The findings indicated that rainfall and temperature are the primary environmental factors influencing Hynobius. Currently, the suitable habitat for the Northeastern China Salamander constitutes 6.6% of the total area of Northeastern China. Projections for the periods of 2050 and 2070 suggest that suitable habitats for the Northeastern China Salamander will continue to expand towards higher latitudes across three climate scenarios. While this study focuses solely on climate change factors and acknowledges certain limitations, it serves as a reliable reference and provides essential information for the distribution and conservation of the Northeastern China Salamander.

Effects of Ultrasound on Reactive Crystallization and Particle Properties of an Aromatic Amine in Batch and Continuous modes

Ultrasound has shown its benefits in the manufacturing processes of many pharmaceuticals and fine chemicals. This study focused on the reactive crystallization system of an aromatic amine and explored the potential uses of ultrasound in both batch and continuous modes. In batch experiments, we studied the effects of different sonication conditions including power, duration, and starting point on final particle properties. Under ultrasound, the crystal form and crystal morphology remained well maintained. The results of particle size and size distribution suggested that ultrasound reduced the mean sizes by improving the nucleation process and breaking up large particles. Additionally, the presence of ultrasound in continuous experiments was capable of inducing nucleation and the crystal products collected had a suitable distribution. Integrating ultrasound into the beginning of the continuous crystallization process can be an alternative to the seeding technique. The increasing sonication power did not reduce the induction time substantially. This indicated that a rational sonication condition should balance the overall process efficiency and energy consumption. The findings from batch and continuous experiments indicate that ultrasound could intensify industrial crystallization of the aromatic amine. Incorporating energy-efficient ultrasound with the continuous process will potentially lead to increased production efficiency and a well-controlled product quality.

Distribution-agnostic landslide hazard modelling via Graph Transformers

In statistical applications, choosing a suitable data distribution or likelihood that matches the nature of the response variable is required. To spatially predict the planimetric area of a landslide population, the most tested likelihood corresponds to the Log-Gaussian case. This causes a limitation that hinders the ability to accurately model both very small and very large landslides, with the latter potentially leading to a dangerous underestimation of the hazard. Here, we test a distribution-agnostic solution via a Graph Transformer Neural Network (GTNN) and implement a loss function capable of forcing the model to capture both the bulk and the right tail of the landslide area distribution. An additional problem with this type of data-driven hazard assessment is that one often excludes slopes with landslide areas equal to zero from the regression procedure, as this may bias the prediction towards small values. Due to the nature of GTNNs, we present a solution where all the landslide area information is passed to the model, as one would expect for architectures built for image analysis. The results are promising, with the landslide area distribution generated by the Wenchuan earthquake being suitably estimated, including both zeros, the bulk and the extremely large cases. We consider this a step forward in the landslide hazard modelling literature, with implications for what the scientific community could achieve in light of a future space–time and/or risk assessment extension of the current protocol.