Layer chicken microbiota:a comprehensive analysis of spatial and temporal dynamics across all major gut sections

Background The gut microbiota influences chicken health,welfare,and productivity.A diverse and balanced microbiota has been associated with improved growth,efficient feed utilisation,a well-developed immune system,disease resistance,and stress tolerance in chickens.Previous studies on chicken gut microbiota have predominantly focused on broiler chickens and have usually been limited to one or two sections of the digestive system,under con-trolled research environments,and often sampled at a single time point.To extend these studies,this investigation examined the microbiota of commercially raised layer chickens across all major gut sections of the digestive system and with regular sampling from rearing to the end of production at 80 weeks.The aim was to build a detailed picture of microbiota development across the entire digestive system of layer chickens and study spatial and temporal dynamics.Results The taxonomic composition of gut microbiota differed significantly between birds in the rearing and pro-duction stages,indicating a shift after laying onset.Similar microbiota compositions were observed between proven-triculus and gizzard,as well as between jejunum and ileum,likely due to their anatomical proximity.Lactobacil-lus dominated the upper gut in pullets and the lower gut in older birds.The oesophagus had a high proportion of Proteobacteria,including opportunistic pathogens such as Gallibacterium.Relative abundance of Gallibacterium increased after peak production in multiple gut sections.Aeriscardovia was enriched in the late-lay phase compared to younger birds in multiple gut sections.Age influenced microbial richness and diversity in different organs.The upper gut showed decreased diversity over time,possibly influenced by dietary changes,while the lower gut,specifi-cally cecum and colon,displayed increased richness as birds matured.However,age-related changes were inconsist-ent across all organs,suggesting the influence of organ-specific factors in microbiota maturation.Conclusion Addressing a gap in previous research,this study explored the microbiota across all major gut sections and tracked their dynamics from rearing to the end of the production cycle in commercially raised layer chickens.This study provides a comprehensive understanding of microbiota structure and development which help to develop targeted strategies to optimise gut health and overall productivity in poultry production.

Spatial compartmentalization and temporal stability of associated microbiota in Pacific oyster Crassostrea gigas

The Pacific oyster Crassostrea gigas,one of the most exploited molluscs in the world,has suffered from massive mortality in recent decades,and the occurrence mechanisms have not been well characterized.In this study,to reveal the relationship of associated microbiota to the fitness of oysters,temporal dynamics of microbiota in the gill,hemolymph,and hepatopancreas of C.gigas during April 2018-January 2019 were investigated by 16 S rRNA gene sequencing.The microbiota in C.gigas exhibited tissue heterogeneity,of which Spirochaetaceae was dominant in the gill and hemolymph while Mycoplasmataceae enriched in the hepatopancreas.Co-occurrence network demonstrated that the gill microbiota exhibited higher inter-taxon connectivity while the hemolymph microbiota had more modules.The richness(Chao 1 index)and diversity(Shannon index)of microbial community in each tissue showed no significant seasonal variations,except for the hepatopancreas having a higher richness in the autumn.Similarly,beta diversity analysis indicated a relatively stable microbiota in each tissue during the sampling period,showing relative abundance of the dominant taxa exhibiting temporal dynamics.Results indicate that the microbial community in C.gigas showed a tissue-specific stability with temporal dynamics in the composition,which might be essential for the tissue functioning and environmental adaption in oysters.This work provides a baseline microbiota in C.gigas and is helpful for the understanding of host-microbiota interaction in oysters.

Elevational and temporal patterns of pollination success in distylous and homostylous buckwheats(Fagopyrum)in the Hengduan Mountains

Reproductive strategies of sexually dimorphic plants vary in response to the environment.Here,we ask whether the sexual systems of Fagopyrum species(i.e.,selfing homostylous and out-crossing distylous)represent distinct adaptive strategies to increase reproductive success in changing alpine environments.To answer this question,we determined how spatial and temporal factors(e.g.,elevation and peak flowering time)affect reproductive success(i.e.,stigmatic pollen load)in nine wild Fagopyrum species(seven distylous and two homostylous)among 28 populations along an elevation gradient of 1299-3315 m in the Hengduan Mountains,southwestern China.We also observed pollinators and conducted hundreds of hand pollinations to investigate inter/intra-morph compatibility,self-compatibility and pollen limitation in four Fagopyrum species(two distylous and two homostylous).We found that Fagopyrum species at higher elevation generally had bigger flowers and more stigmatic pollen loads;lateflowering individuals had smaller flowers and lower pollen deposition.Stigmatic pollen deposition was more variable in distylous species than in homostylous species.Although seed set was not pollenlimited in all species,we found that fruit set was much lower in distylous species,which rely on frequent pollinator visits,than in homostylous species capable of autonomous self-pollination.Our findings that pollination success increases at high elevations and decreases during the flowering season suggest that distylous and homostylous species have spatially and temporally distinct reproductive strategies related to environment-dependent pollinator activity.

Spatial and temporal variation of water clarity in typical reservoirs in the Beijing-Tianjin-Hebei region observed by GF 1-WFV satellite data

Rapidly monitoring regional water quality and the changing trend is of great practical and scientific significance,especially for the Beijing-Tianjin-Hebei(BTH)region of China where water resources are relatively scarce and inland water bodies are generally small.The remote sensing data of the GF 1 satellite launched in 2013 have characteristics of high spatial and temporal resolution,which can be used for the dynamic monitoring of the water environment in small lakes and reservoirs.However,the water quality remote sensing monitoring model based on the GF 1 satellite data for lakes and reservoirs in BTH is still lacking because of the considerable differences in the optical characteristics of the lakes and reservoirs.In this paper,the typical reservoirs in BTH-Guanting Reservoir,Yuqiao Reservoir,Panjiakou Reservoir,and Daheiting Reservoir are taken as the study areas.In the atmospheric correction of GF 1-WFV,the relative radiation normalized atmospheric correction was adopted after comparing it with other methods,such as 6 S and FLAASH.In the water clarity retrieval,a water color hue angle based model was proposed and outperformed other available published models,with the R 2 of 0.74 and MRE of 31.7%.The clarity products of the four typical reservoirs in the BTH region in 2013-2019 were produced using the GF 1-WFV data.Based on the products,temporal and spatial changes in clarity were analyzed,and the main influencing factors for each water body were discussed.It was found that the clarity of Guanting,Daheiting,and Panjiakou reservoirs showed an upward trend during this period,while that of Yuqiao Reservoir showed a downward trend.In the influencing factors,the water level of the water bodies can be an important factor related to the water clarity changes in this region.

Temporal and spatial differences in human activities performed in Urban Green Spaces of Vilnius(Lithuania)

Urban green spaces(UGS)are relevant to city well-being,as recognized by the United Nations’Sustainable Development Goals(SDGs).However,few studies have studied the temporal use of UGS.This work assessed the seasonal,weekly,and daily use of three urban green spaces(Vingis Park,Bernardino Garden,and Jomantas Park)in Vilnius(Lithuania).The study is based on an on-site observation-based survey,which recorded users’characteristics,activities,and weather conditions during summer and winter.The results showed that UGS’s seasonal,weekly,and daily use differed according to park and users’characteristics.Parks with a higher diversity of facilities had a high seasonal difference in the number of observed activities.User numbers were higher in the summer for activities with children,social activities,sports,and water activities than in the winter.Jomantas Park had the lowest variability in user characteristics.Weather variables were linked to changes in users’activities.Higher precipitation and lower temperature were associated with reducing the number of users and the diversity of registered activities.Most of the stationary activities were observed during summer.The diversity of the observed activities was associated with the available facilities rather than the park size.The distribution of stationary activities was spatially correlated with facility/equipment(benches,playgrounds,sports,and fitness equipment)and proximity to water features.The results of this study are relevant for UGS design,planning,and management.

Temporal and Spatial Dynamics of Vaccine-Derived Poliovirus (VDPV) in Democratic Republic of Congo from 2018 to 2023

Background: The Democratic Republic of Congo (DRC) has been facing outbreaks of VDPV since 2017. These wild poliovirus variants are responsible for poliomyelitis, which is in the process of eradication.. In the following lines, we try to show the evolution of VDPV cases across the country in order to understand their chronological dynamics and seasonal influence. Methods: We conducted a cross-sectional study of of VDPV notified in the DRC from 2018 to 2023. Maps of the spatial dynamics of VDPV cases were produced from attack rates with QGIS® (3.22.8). As for temporal dynamics, time series were decomposed and presented in the form of graphs showing the chronological evolution of VDPV cases and their seasonal trend, using R.4.0 software package. Results: A total of 1196 Cases of VDPV types 1, 2 and 3 were recorded in the biological confirmation databases of the INRB and the Expanded Program of Immunization during the study period across25 provinces. The eastern part of the country reporting the most cases. The general trend is upwards, with a peak in 2022 of 527 cases, whereas in 2021 there was a notable drop of 31 cases. Analysis of the temporal breakdown suggests a seasonal pattern, with peaks between the months of September and December, considered being rainy periods in some provinces. Conclusion: During the 6 years of our study (2018 - 2023) almost all the Health Zones were hit by VDPV epidemics. The eastern part was the most impacted. The seasonal component is well marked suggesting a rise in detection in the rainy season and during pivotal periods of climate change.

Spatiotemporal Differentiation of Urban Spatial Form and Carbon Emissions in Poyang Lake City Group

In response to the inherent requirements of low-carbon land spatial planning in Jiangxi Province and the lack of existing research,this paper explored the mechanism of spatial form elements of Poyang Lake urban agglomeration on urban carbon emissions.Based on generalized linear regression and geographically weighted regression models,this paper analyzed the spatiotemporal distribution characteristics of carbon emissions,the spatiotemporal relationship between urban form index and carbon emissions,and the spatial differentiation of the intensity of dominant factors from 63 county-level administrative units in the Poyang Lake city group from 2005 to 2020.The results showed that:①The carbon emissions of urban agglomerations around Poyang Lake are generally increasing,and the spatial distribution of carbon emissions is characterized by high-value concentration in the middle and low-value agglomeration in pieces;②The main driving factor for the spatial heterogeneity of carbon emissions was the expansion of built-up area;③Improving urban compactness and optimizing urban form could effectively reduce urban carbon emissions.The results showcased the correlation between urban spatial landscape pattern and the spatiotemporal distribution of carbon emissions,which could make the low-carbon land spatial planning in the Poyang Lake city group more reasonable and practical.

Spatial and Temporal Distribution Characteristics of Snowstorm in Ulanqab City in Recent 30 Years

Based on the data of daily snowfall and weather phenomena of 11 national meteorological stations in Ulanqab City from 1991 to 2020,the spatial and temporal distribution characteristics of snowstorm were analyzed.The results show that the snowstorm in Ulanqab had obvious seasonal distribution characteristics,mainly happening in spring(March-May)and autumn(September-November).It also had obvious regional distribution in space,and the snowstorm center appeared in Chahar Right Wing Middle Banner and Jining District,namely the east side of the Yinshan Mountain.In the past 30 years,the amount of snowstorm in the whole year in Ulanqab showed a certain fluctuation trend,and the number of snowstorm days had shown an obvious upward trend since 2011.

Evaluation of COVID-19 Cases and Vaccinations in the State of Georgia, United States: A Spatial Perspective

This study evaluates the distribution of COVID-19 cases and mass vaccination campaigns from January 2020 to April 2023. There are over 235,000 COVID-19 cases and over 733,000 vaccinations across the 159 counties in the state of Georgia. Data on COVID-19 was acquired from usafact.org while the vaccination records were obtained from COVID-19 vaccination tracker. The spatial patterns across the counties were analyzed using spatial statistical techniques which include both global and local spatial autocorrelation. The study further evaluates the effect of vaccination and selected socio-economic predictors on COVID-19 cases across the study area. The result of hotspot analysis reveals that the epicenters of COVID-19 are distributed across Cobb, Fulton, Gwinnett, and DeKalb counties. It was also affirmed that the vaccination records followed the same pattern as COVID-19 cases’ epicenters. The result of the spatial error model performed well and accounted for a considerable percentage of the regression with an adjusted R squared of 0.68, Akaike Information Criterion (AIC) 387.682 and Breusch-Pagan of 9.8091. ESDA was employed to select the main explanatory variables. The selected variables include vaccination, population density, percentage of people that do not have health insurance, black race, Hispanic and these variables accounted for 68% of the number of COVID-19 cases in the state of Georgia during the study period. The study concludes that both COVID-19 cases and vaccinated individuals have spatial peculiarities across counties in Georgia state. Lastly, socio-economic variables and vaccination are very important to reduce the vulnerability of individuals to COVID-19 disease.

Examining the Spatiotemporal Dynamics and Determinants of Land Urbanization in Prefecture-level Cities,China

Examining the spatiotemporal dynamics and determinants of land urbanization is critical for promoting healthy urban development and the rational use of land resources.Based on the dataset consisting of land use change data and selected factors in 2010 and2020,this study used visual analysis to reveal the spatiotemporal dynamics of land urbanization across prefecture-level cities in China.Meanwhile,the driving forces underlying land urbanization were examined by using geographical detector technique.Following are the findings:1)we find that there exist notable spatial variances in land urbanization across prefecture-level cities.Currently,the differentiation in land urbanization between the northern and southern cities is more pronounced than that between the coastal and inland cities,or between the eastern and western cities.Prefecture-level cities located in central and western China have experienced the most rapid growth in land urbanization.Conversely,the growth rate in northeastern China is the lowest,while the velocity in eastern China remains relatively stable.By using spatial autocorrelation analysis,this study reveals that the land urbanization level in prefecture-level cities has significant spatial agglomeration.2)We further find that land urbanization in China is influenced by factors related to urban land supply and demand,and urban population growth,economic growth,land financial and political incentive have greater impact on land urbanization than other factors.3)We also find that the impacts of determinants on China’s land urbanization vary over time,the explanatory power of economic development increased,while the explanatory power of state forces declined.We argue that integrating the supply and demand factors of land urbanization can provide a more comprehensive understanding of the driving mechanisms underlying land urbanization in China and other transitional countries,and help decision-makers in these countries formulate more detailed and specific land urbanization policies.

Spatial heterogeneity and driving mechanism of urban climbing and its impact on regional environment in varied landform types in the middle reaches of the Yellow River

Urbanization research is essential for the sustainable use of regional land resources and ecological environment protection.The expansion process and driving factors of urban construction land at different scales in the middle reaches of the Yellow River(MRYR)have not been comprehensively elucidated.In this study,we explored the distribution pattern of urban construction land on different slope gradients at different scales and analyzed its influencing factors.The main findings were as follows:(1)There has been significant expansion of urban construction land in the MRYR over the past 20 years.Spatial heterogeneity was observed in the regional urban construction land expansion process among different geomorphic regions.(2)The urban construction land in the MRYR was expanded vertically to areas with slopes of>5°,particularly in 2005–2010.Significant slope climbing of urban construction land was observed in the loess hilly-gully and rocky mountain areas.(3)In MRYR,68.45%of the counties were categorized as the slope-climbing types,including 37.38%high-slope-climbing types.(4)The regional population density and economic development level were closely associated with regional urban construction land area variability.(5)The climbing process of regional urban construction can effectively alleviate farmland encroachment and pressure on the regional ecological environment.The urban expansion of the metropolitan distribution areas in the Plain region(such as Xi'an,Taiyuan)had a relatively significant impact on the local carbon storage.

The Spatiotemporal Distribution Characteristics of Cloud Types and Phases in the Arctic Based on CloudSat and CALIPSO Cloud Classification Products

The cloud type product 2B-CLDCLASS-LIDAR based on CloudSat and CALIPSO from June 2006 to May 2017 is used to examine the temporal and spatial distribution characteristics and interannual variability of eight cloud types(high cloud, altostratus, altocumulus, stratus, stratocumulus, cumulus, nimbostratus, and deep convection) and three phases(ice,mixed, and water) in the Arctic. Possible reasons for the observed interannual variability are also discussed. The main conclusions are as follows:(1) More water clouds occur on the Atlantic side, and more ice clouds occur over continents.(2)The average spatial and seasonal distributions of cloud types show three patterns: high clouds and most cumuliform clouds are concentrated in low-latitude locations and peak in summer;altostratus and nimbostratus are concentrated over and around continents and are less abundant in summer;stratocumulus and stratus are concentrated near the inner Arctic and peak during spring and autumn.(3) Regional averaged interannual frequencies of ice clouds and altostratus clouds significantly decrease, while those of water clouds, altocumulus, and cumulus clouds increase significantly.(4) Significant features of the linear trends of cloud frequencies are mainly located over ocean areas.(5) The monthly water cloud frequency anomalies are positively correlated with air temperature in most of the troposphere, while those for ice clouds are negatively correlated.(6) The decrease in altostratus clouds is associated with the weakening of the Arctic front due to Arctic warming, while increased water vapor transport into the Arctic and higher atmospheric instability lead to more cumulus and altocumulus clouds.

Spatial pattern recognition for near-surface high temperature increases in mountain areas using MODIS and SRTM DEM

Abrupt near-surface temperature changes in mountainous areas are a special component of the mountain climate system.Fast and accurate measurements of the locations,intensity,and width of the near-surface changes are necessary but highly difficult due to the complicated environmental conditions and instrumental issues.This paper develops a spatial pattern recognition method to measure the near-surface high temperature increase(NSHTI),one of the lesser-attended changes.First,raster window measurement was proposed to calculate the temperature lapse rate using MODIS land surface temperature and SRTM DEM data.It fully considers the terrain heights of two neighboring cells on opposite or adjacent slopes with a moving window of 3×3 cell size.Second,a threshold selection was performed to identify the NSHTI cells using a threshold of-0.65℃/100 m.Then,the NSHTI strips were parameterized through raster vectorization and spatial analysis.Taking Yunnan,a mountainous province in southwestern China,as the study area,the results indicate that the NSHTI cells concentrate in a strip-like pattern along the mountains and valleys,and the strips are almost parallel to the altitude contours with a slight northward uplift.Also,they are located mostly at a 3/5 height of high mountains or within 400 m from the valley floors,where the controlling topographic index is the altitude of the terrain trend surface but not the absolute elevation and the topographic uplift height and cutting depth.Additionally,the NSHTI intensity varies with the geographic locations and the proportions increase with an exponential trend,and the horizontal width has a mean of about 1000 m and a maximum of over 5000 m.The result demonstrates that the proposed method can effectively recognize NSHTI boundaries over mountains,providing support for the modeling of weather and climate systems and the development of mountain resources.

Study on the Spatiotemporal Pattern Evolution and Influencing Factors of Population Aging in Henan Province

This study utilized census data from Henan Province for the years 2000,2010,and 2020 to investigate the spatiotemporal evolution of population aging,defined by the proportion of the population aged 65 and above.Employing spatial analysis techniques such as spatial autocorrelation and the standard deviation ellipse,the research mapped out the progression and distribution of aging demographics.Furthermore,the study delved into the influencing factors of aging using an optimal parameters-based geographical detector.Results indicate a deepening degree of population aging in Henan Province,transitioning from an adult type to an old type structure.There is a marked positive spatial correlation among counties,with high-value aging areas initially decreasing,then increasing,and notably spreading from the central to the central and southern regions of the province.The center of gravity for population aging,specifically around Changge City and Xuchang City,exhibits a trajectory moving southeast before shifting northwest.Factor detection reveals that in 2000,2010,and 2020,the elderly dependency ratio predominantly influences the aging trend,with explanatory powers of 88.4%,87.9%,and 90.9%,respectively.Interaction analysis indicates that the interaction between the old-child ratio and the elderly dependency ratio has a strong explanatory power for the aging patterns in Henan Province,reaching 97.3%,97.0%,and 97.4%,respectively.

Analysis of Spatiotemporal Changes in Integrated Land Productivity in Chongqing from 1997 to 2023

[Objectives]Integrated land productivity can reflect the comprehensive utilization of land and the overall output level,which is the most basic and commonly used indicator in assessing land use efficiency.This thesis aims to analyze the spatial and temporal changes of integrated land productivity in Chongqing from 1997 to 2023 in order to assess its land use efficiency.[Methods]This study measured the integrated land productivity of Chongqing Municipality,the only municipality directly under the central government in the western part of China,over the past 26 years(1997-2023)through relevant surveys and statistical data,and analyzed in depth the integrated land productivity of the 38 districts and counties under the jurisdiction of Chongqing,as well as the functional sub-districts of the"one district and two clusters"and the"one district and two clusters"in Chongqing.It also analyzes the characteristics of spatial and temporal differences in land productivity in 38 districts and counties under the jurisdiction of Chongqing and"one district and two clusters".[Results]The results of the study show that over the past 26 years,the integrated land productivity of Chongqing has shown an annual growth trend,and the integrated land productivity of the 38 districts and counties and the functional subregions of"one district and two clusters"has also increased significantly,but the average annual growth rate of the integrated land productivity varies among different regions.From the perspective of spatial differences,there are significant differences in land productivity among the 38 districts and counties of Chongqing and the functional subregions of"one district and two clusters",which are mainly due to the different natural conditions,economic development levels and functional positioning of each region.[Conclusions]Based on the results of the study and the actual situation of Chongqing,this paper puts forward the leading measures to improve the integrated land productivity,with a view to providing a reference basis for Chongqing to improve the efficiency of land use and promote the sustainable use of land resources.

Spatial patterns of Picea crassifolia driven by environmental heterogeneity and intraspecifi c interactions

Research on the spatial patterns of tree populations is critical for understanding the structure and dynamic processes of forests.However,little is known about how the underlying drivers shape these patterns and species interactions in forest systems.In this study,spatial point pattern analysis investigated the combined eff ects of intraspecifi c interactions and environmental heterogeneity on the spatial structure and internal maintenance mechanisms of Picea crassifolia in the Qilian Mountain National Nature Reserve,China.Data were obtained from a 10.2-ha dynamic monitoring plot(DMP)and sixteen 0.04-ha elevation gradient plots(EGPs).Under complete spatial randomness,both mature trees and saplings in the DMP demonstratedlarge-scale aggregation with negative correlations.In EGPs,saplings were clustered in small mesoscales,mature trees were randomly distributed,and the interactions of saplingstrees at all elevations were not correlated.By eliminating the interference of environmental heterogeneity through the inhomogeneous Poisson process,saplings in the DMP and EGPs were clustered in small scales and trees randomly distributed.Intraspecifi c associations were negatively correlated,in the DMP and at low elevations,and no correlations in high elevations of EGPs.In the vertical scale,saplings showed a small-scale aggregation pattern with increase in elevation,and the aggregation degree fi rst decreased and then increased.The interactions of saplings-trees and saplings–saplings showed inhibitions at small scales,with the degree of inhibition gradually decreasing.Spatial patterns and associations of adults–adults did not change signifi-cantly.The results revealed that intraspecifi c interactions and environmental heterogeneity regulated the spatial patterns of P.crassifolia at small and large scales,respectively.Environmental heterogeneity might be the most decisive factor aff ecting the spatial patterns of saplings,while trees were more aff ected by intraspecifi c interactions.Moreover,competition between trees in this area could be more common than facilitation for the growth and development of individuals.

Optimizing Spatial Pattern Analysis in Serial Remote Sensing Images through Empirical Mode Decomposition and Ant Colony Optimization

Serial remote sensing images offer a valuable means of tracking the evolutionary changes and growth of a specific geographical area over time.Although the original images may provide limited insights,they harbor considerable potential for identifying clusters and patterns.The aggregation of these serial remote sensing images(SRSI)becomes increasingly viable as distinct patterns emerge in diverse scenarios,such as suburbanization,the expansion of native flora,and agricultural activities.In a novel approach,we propose an innovative method for extracting sequential patterns by combining Ant Colony Optimization(ACD)and Empirical Mode Decomposition(EMD).This integration of the newly developed EMD and ACO techniques proves remarkably effective in identifying the most significant characteristic features within serial remote sensing images,guided by specific criteria.Our findings highlight a substantial improvement in the efficiency of sequential pattern mining through the application of this unique hybrid method,seamlessly integrating EMD and ACO for feature selection.This study exposes the potential of our innovative methodology,particularly in the realms of urbanization,native vegetation expansion,and agricultural activities.

Flight parameter calculation method of multi-projectiles using temporal and spatial information constraint

The dynamic parameters of multiple projectiles that are fired using multi-barrel weapons in highfrequency continuous firing modes are important indicators to measure the performance of these weapons.The characteristics of multiple projectiles are high randomness and large numbers launched in a short period of time,making it very difficult to obtain the real dispersion parameters of the projectiles due to the occlusion or coincidence of multiple projectiles.Using six intersecting-screen testing system,in this paper,we propose an association recognition and matching algorithm of multiple projectiles using a temporal and spatial information constraint mechanism.We extract the output signal from each detection screen and then use the wavelet transform to process the output signal.We present a method to identify and extract the time values on which the projectiles pass through the detection screens using the wavelet transform modulus maximum theory.We then use the correlation of the output signals of three parallel detection screens to establish a correlation coefficient recognition constraint function for the multiple projectiles.Based on the premise of linear projectile motion,we establish a temporal and spatial constraint matching model using the projectile’s position coordinates in each detection screen and the projectile’s time constraints within the multiple intersecting-screen geometry.We then determine the time values of the multiple projectiles in each detection screen using an iterative search cycle registration,and finally obtain the flight parameters for the multiple projectiles in the presence of uncertainty.The proposed method and algorithm were verified experimentally and can solve the problem of uncertainty in projectiles flight parameter under different multiple projectile firing states.

Deepfake Video Detection Based on Improved CapsNet and Temporal–Spatial Features

Rapid development of deepfake technology led to the spread of forged audios and videos across network platforms,presenting risks for numerous countries,societies,and individuals,and posing a serious threat to cyberspace security.To address the problem of insufficient extraction of spatial features and the fact that temporal features are not considered in the deepfake video detection,we propose a detection method based on improved CapsNet and temporal–spatial features(iCapsNet–TSF).First,the dynamic routing algorithm of CapsNet is improved using weight initialization and updating.Then,the optical flow algorithm is used to extract interframe temporal features of the videos to form a dataset of temporal–spatial features.Finally,the iCapsNet model is employed to fully learn the temporal–spatial features of facial videos,and the results are fused.Experimental results show that the detection accuracy of iCapsNet–TSF reaches 94.07%,98.83%,and 98.50%on the Celeb-DF,FaceSwap,and Deepfakes datasets,respectively,displaying a better performance than most existing mainstream algorithms.The iCapsNet–TSF method combines the capsule network and the optical flow algorithm,providing a novel strategy for the deepfake detection,which is of great significance to the prevention of deepfake attacks and the preservation of cyberspace security.

Spatio-Temporal Change of Dispersal Areas of Greater Kudu (Tragelaphus strepsiceros) in Lake Bogoria Landscape, Kenya

Decline in wildlife populations is manifest globally, regionally and locally. A wildlife decline of 68% has been reported in Kenya’s rangelands with Baringo County experiencing more than 85% wildlife loss in the last four decades. Greater Kudu (Tragelaphus strepsiceros) is endemic to Lake Bogoria landscape in Baringo County and constitutes a major tourist attraction for the region necessitating use of its photo on the County’s logo and thus a flagship species. Tourism plays a central role in Baringo County’s economy and is a major source of potential growth and employment creation. The study was carried out to assess spatio-temporal change of dispersal areas of Greater Kudu (GK) in Lake Bogoria landscape in the last four years for enhanced adaptive management and improved livelihoods. GK population distribution primary data collected in December 2022 and secondary data acquired from Lake Bogoria National Game Reserve (LBNGR) for 2019 and 2020 were digitized using in a Geographic Information System (GIS). Measures of dispersion and point pattern analysis (PPA) were used to analyze dispersal of GK population using GIS. Spatio-temporal change of GK dispersal in LBNR was evident thus the null hypothesis was rejected. It is recommended that anthropogenic activities contributing to GK’s habitat degradation be curbed by providing alternative livelihood sources and promoting community adoption of sustainable technologies for improved livelihoods.