Diversity and Influence of Environmental Factors on the Spatio-Temporal Distribution of the Ichthyofauna of Malonda Lagoon (Congo Brazzaville)

This study was initiated with the aim of studying the diversity and spatio-temporal distribution of fish in the Malonda lagoon, one of the coastal ecosystems of the Base Guinea in the Republic of Congo. The fish were sampled over a period of two years in three zones each including three stations known as: Mangrove, Grass and Full water. One station upstream towards the freshwater zone, one station downstream towards the mouth and one station in the containment zone. The catches were made using monofilament gillnets of 8, 10, 20 and 30 mm mesh size. During the rainy season, 1516 specimens belonging to 29 species, 17 families and 12 orders were collected. In the dry season, 768 specimens belonging to 20 species, 11 families and 8 orders were collected. For both seasons, the family Cichlidae is the most diversified. The marine forms are the most represented compared to the continental forms. Redundancy Analysis with forward selection coupled with Monte Carlo permutation tests showed that in the rainy season four variables influenced the distribution of species (Depth: 48%, Vase: 16%, Nitrogen: 10% and Transparency: 10%);in the dry season three variables influenced the distribution of species (Vase: 38%, Nitrogen: 14% and Oxygen: 11%). Ecological indices showed that the Malonda lagoon is already undergoing either anthropic or natural impacts, its state of ecological integrity is disturbed, the values of Shannon diversity and Equitability indices are not close to maximum values. The results of this study will serve as an ecological database for the proper management of these ecosystems.

Warhead fragments motion trajectories tracking and spatio-temporal distribution reconstruction method based on high-speed stereo photography

High speed photography technique is potentially the most effective way to measure the motion parameter of warhead fragment benefiting from its advantages of high accuracy,high resolution and high efficiency.However,it faces challenge in dense objects tracking and 3D trajectories reconstruction due to the characteristics of small size and dense distribution of fragment swarm.To address these challenges,this work presents a warhead fragments motion trajectories tracking and spatio-temporal distribution reconstruction method based on high-speed stereo photography.Firstly,background difference algorithm is utilized to extract the center and area of each fragment in the image sequence.Subsequently,a multi-object tracking(MOT)algorithm using Kalman filtering and Hungarian optimal assignment is developed to realize real-time and robust trajectories tracking of fragment swarm.To reconstruct 3D motion trajectories,a global stereo trajectories matching strategy is presented,which takes advantages of epipolar constraint and continuity constraint to correctly retrieve stereo correspondence followed by 3D trajectories refinement using polynomial fitting.Finally,the simulation and experimental results demonstrate that the proposed method can accurately track the motion trajectories and reconstruct the spatio-temporal distribution of 1.0×10^(3)fragments in a field of view(FOV)of 3.2 m×2.5 m,and the accuracy of the velocity estimation can achieve 98.6%.

Spatio-temporal distribution of net primary productivity along the northeast China transect and its response to climatic change

An improved Carnegie Ames Stanford Approach model （CASA model） was used to estimate the net primary productivity （NPP） of the Northeast China Transect （NECT） every month from 1982 to 2000. The spatial-temporal distribution of NPP along NECT and its response to climatic change were also analyzed. Results showed that the change tendency of NPP spatial distribution in NECT is quite similar to that of precipitation and their spatial correlation coefficient is up to 0.84 （P 〈 0.01）. The inter-annual variation of NPP in NECT is mainly affected by the change of the aestival NPP every year, which accounts for 67.6% of the inter-annual increase in NPP and their spatial correlation coefficient is 0.95 （P 〈 0.01）. The NPP in NECT is mainly cumulated between May and September, which accounts for 89.8% of the annual NPP. The NPP in summer （June to August） accounts for 65.9% of the annual NPP and is the lowest in winter. Recent climate changes have enhanced plant growth in NECT. The mean NPP increased 14.3% from 1980s to 1990s. The inter-annual linear trend of NPP is 4.6 gC·m^-2·a^-1, and the relative trend is 1.17%, which owns mainly to the increasing temperature.

Analysis on Spatio-temporal Distribution of Lightning in Dalian Area of China between 2007 and 2008

The cloud-to-ground lightning data between 2007 and 2008 were collected by lightning detection and location system,which was composed of four lightning detectors in four different sites of Dalian area.The spatio-temporal distribution of cloud-to-ground lightning in surrounding areas of Dalian was analyzed from several aspects of polarity distribution,diurnal variation,lightning intensity and lightning density.The results showed that the number of negative lightning accounted for 93.9% of the total number of lightning,and its average lightning intensity was 27.99 kA.The number of positive lightning accounted for 6.1% of the total number of lightning,and its average lightning intensity was 35.56 kA.The diurnal variation of lightning frequency showed an obvious structure of two peaks (17:00-18:00 and 04:00-05:00) and two valleys (09:00-10:00 and 00:00-01:00).The number of lightning between May and September was 91.5% of the annual number,and the lightning occurred the most frequently between June and August.Most of positive and negative lightning was at the intensity of 15-35 kA,80.0% lower than 40 kA,and 99.3% lower than 100 kA.The lightning density had obvious regional differences in distribution,high in the Liaodong Bay and the Dalian Bay and low in inland areas.Therefore,coastal areas should attract more attention in lightning disaster defense in the surrounding areas of Dalian.

Differential distribution of PINK1 and Parkin in the primate brain implies distinct roles

The vast majority of in vitro studies have demonstrated that PINK1 phosphorylates Parkin to work together in mitophagy to protect against neuronal degeneration.However,it remains largely unclear how PINK1 and Parkin are expressed in mammalian brains.This has been difficult to address because of the intrinsically low levels of PINK1 and undetectable levels of phosphorylated Parkin in small animals.Understanding this issue is critical for elucidating the in vivo roles of PINK1 and Parkin.Recently,we showed that the PINK1 kinase is selectively expressed as a truncated form(PINK1–55)in the primate brain.In the present study,we used multiple antibodies,including our recently developed monoclonal anti-PINK1,to validate the selective expression of PINK1 in the primate brain.We found that PINK1 was stably expressed in the monkey brain at postnatal and adulthood stages,which is consistent with the findings that depleting PINK1 can cause neuronal loss in developing and adult monkey brains.PINK1 was enriched in the membrane-bound fractionations,whereas Parkin was soluble with a distinguishable distribution.Immunofluorescent double staining experiments showed that PINK1 and Parkin did not colocalize under physiological conditions in cultured monkey astrocytes,though they did colocalize on mitochondria when the cells were exposed to mitochondrial stress.These findings suggest that PINK1 and Parkin may have distinct roles beyond their well-known function in mitophagy during mitochondrial damage.

Spatio-temporal distribution of malaria vectors(Diptera:Culicidae) across different climatic zones of Iran

Malaria is a main vector-borne public health problem in Iran.The last studies on Iranian mosquitoes show 31 Anopheles species including different sibling species and genotypes,eight of them are reported to play role in malaria transmission.The objective of this study is to provide a reference for malaria vectors of Iran and to map their spatial and temporal distribution in different climatic zones.Shape files of administrative boundaries and climates of Iran were provided by National Cartographic Center.Data on distribution and seasonal activity of malaria vectors were obtained from different sources and a databank in district level was created in Excel 2003, inserted to the shape files and analyzed by ArcGIS 9.2 to provide the maps.Anopheles culicifacies Giles s.l.,Anopheles dthali Patton,Anopheles fluviatilis James s.L,Anopheles maculipennis Meigen s.L,Anopheles sacharovi Favre,Anopheles stephensi IJston,and Anopheles superpictus Grassi have been introduced as primary and secondary malaria vectors and Anopheles puicherrimus Theobald as a suspected vector in Iran.Temporal distribution of anopheline mosquitoes is restricted to April_December in northern Iran,however mosquitoes can be found during the year in southern region.Spatial distribution of malaria vectors is different based on species,thus six of them(except for Anopheles maculipennis s.l.and Anopheles sacharovi) are reported from endemic malarious area in southern and southeastern areas of Iran.The climate of this part is usually warm and humid,which makes it favorable for mosquito rearing and malaria transmission.Correlation between climate conditions and vector distribution can help to predict the potential range of activity for each species and preparedness for malaria epidemics.

Root growth and spatio-temporal distribution of three common annual halophytes in a saline desert, northern Xinjiang

Root growth and spatial and temporal distribution in the 0-100 cm soil profiles of three common annual halophytes Salsola subcrassa, Suaeda acuminate and Petrosimonia sibirica distributed in a saline desert in north- ern Xinjiang, China were studied in 2009 and 2010. The results showed that the root systems of the three halo- phytes were of the taproot type, vertically distributed in the 90-cm soil profile, and were deepest in late July. Their taproots reached maximum depth rapidly, early in the growth period, but with rare lateral roots. They were then dug out in an orderly way, from bottom to top, exhibiting vertical development first and then horizontal development. The distribution of specific root length, which reflects the characteristics of the feeder root, was gradually increased from top to bottom, whereas root weight displayed an opposite distribution pattern. The root length distribution of the three halophytes was concentrated （62% to 76%） in the middle soil profile （20-60 cm）, with less distribution in the surface （0-20 cm） and bottom （60-90 cm） soil profiles. The results indicated that the roots of the three annual halophytes grew rapidly into the deeper soil layer after germination, which ensured the plant survival and uptake of water and nutrition, and thus built up a strong tolerance to an arid, high-salt environment.

Spatio-temporal distribution of vegetation index and its influencing factors——a case study of the Jiaozhou Bay, China

The coastal zone is an area characterized by intense interaction between land and sea, high sensitivity to regional environmental changes, and concentrated human activities. Little research has investigated vegetation cover changes in coastal zones resulting from climate change and land-use change, with a lack of knowledge about the driving mechanism. Normalized diff erence vegetation index(NDVI) can be used as an indicator for change of the coastal environment. In this study, we analyzed the interannual changes and spatial distribution of NDVI in the coastal zone around Jiaozhou Bay in Qingdao, a coastal city undergoing rapid urbanization in northeast China. The underlying causes of NDVI variations were discussed in the context of climate change and land-use change. Results showed that the spatio-temporal distribution of NDVI displayed high spatial variability in the study area and showed a typical trend of gradually increasing from coastal to inland regions. The significant increase area of NDVI was mainly found in newly added construction land, extending along the coastline towards the inland. Land vegetation cover demonstrated a certain response relationship to sea-land climate change and land-based activities. The impact of land-based human activities was slightly greater than that of sea-land climate change for land vegetation cover. The results indicate that promoting ecological policies can build an ecological security framework of vegetation suitable for the resource characteristics of coastal cities. The framework will buf fer the negative ef fects of sea-land climate change and land-based human activities on vegetation cover and thereby achieve the balance of regional development and ecological benefits in the coastal zone.

Integrated approach for understanding spatio-temporal changes in forest resource distribution in the central Himalaya

Intense anthropogenic exploitation has altered distribution of forest resources. This change was analyzed using visual interpretation of satellite data of 1979, 1999 and 2009. Field and interactive social surveys were conducted to identify spatial trends in forest degradation and data were mapped on forest cover and land use maps. Perceptions of villagers were compiled in a pictorial representation to understand changes in forest resource distribution in central Himalaya from 1970 to 2010. For- ested areas were subject to degradation and isolation due to loss of con- necting forest stands. Species like Lantana camara and Eupatorium adenophorum invaded forest landscapes. Intensity of human pressure differed by forest type and elevation. An integrated approach is needed to monitor forest resource distribution and disturbance.

Effects of spatio-temporal and environmental factors on distribution and abundance of wintering anchovy Engraulis japonicus in central and southern Yellow Sea

We investigated the spatio-temporal and environmental factors that affect the distribution and abundance of wintering anchovy and quantifi es the infl uences of these factors. Generalized additive models(GAMs) were developed to examine the variation in species distribution and abundance with a set of spatiotemporal and oceanographic factors, using data collected by bottom trawl surveys and remote sensing in the central and southern Yellow Sea during 2000–2011. The fi nal model accounted for 28.21% and 41.03% of the variance in anchovy distribution and abundance, respectively. The results of a two-step GAM showed that hour, longitude, latitude, temperature gradient(TGR), and chlorophyll a(Chl- a) concentration best explained the anchovy distribution(presence/absence) and that a model including year, longitude, latitude, depth, sea surface temperature(SST), and TGR best described anchovy abundance(given presence). Longitude and latitude were the most important factors affecting both distribution and abundance, but the area of high abundance tended to be east and south of the area where anchovy were most likely to be present. Hour had a signifi cant effect on distribution, but year was more important for anchovy abundance, indicating that the anchovy catch ratio varied across the day but abundance had an apparent interannual variation. With respect to environmental factors, TGR and Chl- a concentration had effects on distribution, while depth, SST, and TGR affected abundance. Changes in SST between two successive years or between any year and the 2000–2011 mean were not associated with changes in anchovy distribution or abundance. This fi nding indicated that short- and long-term water temperature changes during 2000–2011 were not of suffi cient magnitude to give rise to variation in wintering anchovy distribution or abundance in the study area. The results of this study have important implications for fi sheries management.

Response of Spatio-temporal Distribution of Fishery Resources to Mairne Environment in the Northern South China Sea

[Objective] The paper was to investigate the spatio-temporal distribution of fishery resources in the northern South China Sea and to provide reference for scientific evaluation and effective protection of fishery resources in the northern South China Sea. [Methods] Based on monitoring data and satellite remote sensing data [including Sea Surface Temperature(SST), Chlorophyll a concentration(Chl a) and Sea Surface Wind(SSW)] in winter(January to February) and summer(August to September) in the northern South China Sea, the relationship between spatio-temporal distribution of fishery resources and marine environment was investigated by using Generalized Linear Models(GLM), fishing ground gravity and correlation analysis. [Results] The suitable SST and Chl a of light falling-net fishing ground in winter were 17-23°C and 0.2-0.6 mg/m3, respectively. The suitable SST and Chl a in summer were approximately 28°C and 0.2-1.0 mg/m3. Standardized Catch Per Unit Effort(SCPUE) was higher in summer(2-4) and lower in winter(1-3). From winter to summer, the fishing ground gravity migrated to the east about 1 °E. [Conclusion] The spatio-temporal distribution of fishery resources is related to eastern Hainan-western Guangdong upwelling and the coastal flow, caused by the monsoon in the northern South China Sea, and the major catch species of light falling-net.

Spatio-Temporal Distribution of Agricultural Non-Point Source Pollution in Binzhou City Based on Large Computer Data

Based on the relevant statistics on the agricultural non-point source pollution in Binzhou City,we studied the spatio-temporal variation in agricultural non-point source nitrogen pollution and phosphorus pollution in Binzhou City during 2008-2015. The results showed that the agricultural non-point source nitrogen pollution and phosphorus pollution in Binzhou City changed from 114400 t and 28800 t in 2008 to110600 t and 24400 t in 2015,respectively; for the non-point source nitrogen pollution sources,the proportion of chemical fertilizer,manure and domestic sewage changed from 80. 41%,10. 47% and 9. 13% in 2008 to 82. 94%,4. 77% and 12. 29% in 2015,respectively; for the non-point source phosphorus pollution sources,the proportion of chemical fertilizer,manure and domestic sewage changed from 89. 29%,8. 32% and 2. 39% in 2008 to 91. 6%,4. 78% and 3. 62% in 2015,respectively; in 2015,the non-point source nitrogen pollution was most serious in Wudi County and Huimin County and least serious in Zhanhua County; the non-point source phosphorus pollution was most serious in Zouping County and least serious in Wudi County.

Implementing geostatistical analysis to study spatio-temporal distribution patterns of swimming crabs(Portunus trituberculatus)

This study attempted to compare the performance of local polynomial interpolation,inverse distance weighted interpolation,and ordinary kriging in studying distribution patterns of swimming crabs.Cross-validation was used to select the optimum method to get distribution results,and kriging was used for making spatial variability analysis.Data were collected from 87 sampling stations in November of 2015(autumn)and February(winter),May(spring)and August(summer)of 2016.Results indicate that swimming crabs widely distributed in autumn and summer:in the summer,they were more spatially independent,and resources in each sampling station varied a lot;in the winter and spring,the abundance of crabs was much lower,but the individual crab size was bigger,and they showed the patchy and more concentrative distribution pattern,which means they were more spatially dependent.Distribution patterns were in accordance with ecological migration features of swimming crabs,which were affected by the changing marine environment.This study could infer that it is applicable to study crab fishery or even other crustacean species using geostatistical analysis.It not only helps practitioners have a better understanding of how swimming crabs migrate from season to season,but also assists researchers in carrying out a more comprehensive assessment of the fishery.Therefore,it may facilitate advancing the implementation in the pilot quota management program of swimming crabs in northern Zhejiang fishing grounds.

Spatio-temporal distribution of Konosirus punctatus spawning and nursing ground in the South Yellow Sea

In recent years,Konosirus punctatus has accounted for a large portion in catch composition and become important economic species in the South Yellow Sea.However,the distribution of K.punctatus early life stages is still poorly understood.In this study,generalized additive models with Tweedie distribution were used to analyze the relationships between K.punctatus ichthyoplankton and environmental factors(longitude and latitude,sea surface temperature(SST),sea surface salinity(SSS)and depth),and predict distribution K.punctatus spawning ground and nursing ground,based on samplings collected in 6 months during 2014–2017.The results showed that K.punctatus’spawning ground were mainly distributed in central and north study area(from 33.0°N to 37.0°N).By comparison,the nursing ground shifted southward,which were approximately located along central and south coast of study area(from 31.7°N to 35.5°N).The optimal models identified that suitable SST,SSS and depth for eggs were 19–26℃,25–30 and 9–23 m,respectively.The suitable SSS for larvae were 29–31.The K.punctatus spawning habit might have changed in the past decades,which was a response to increasing SST and fishing pressure.That needs to be proved in further study.The study provides references of conservation and exploitation for K.punctatus.

The Influence of Climate Change and Variability on Spatio-Temporal Rainfall and Temperature Distribution in Zanzibar

Climate change has resulted in serious social-economic ramifications and extremely catastrophic weather events in the world, Tanzania and Zanzibar in particular, with adaptation being the only option to reduce impacts. The study focuses on the influence of climate change and variability on spatio-temporal rainfall and temperature variability and distribution in Zanzibar. The station observation datasets of rainfall, Tmax and Tmin acquired from Tanzania Meteorological Authority (TMA) and the Coordinated Regional Climate Downscaling Experiment program (CORDEX) projected datasets from the Regional climate model HIRHAM5 under driving model ICHEC-EC-EARH, for the three periods of 1991-2020 used as baseline (HS), 2021-2050 as near future (NF) and 2051-2080 far future (FF), under two representative concentration pathways (RCP) of 4.5 and 8.5, were used. The long-term observed Tmax and Tmin were used to produce time series for observing the nature and trends, while the observed rainfall data was used for understanding wet and dry periods, trends and slope (at p ≤ 0.05) using the Standardized Precipitation Index (SPI) and the Mann Kendall test (MK). Moreover, the Quantum Geographic Information System (QGIS) under the Inverse Distance Weighting (IDW) interpolation techniques were used for mapping the three decades of 1991-2000 (hereafter D1), 2001-2010 (hereafter D2) and 2011-2020 (hereafter D3) to analyze periodical spatial rainfall distribution in Zanzibar. As for the projected datasets the Climate Data Operator Commands (CDO), python scripts and Grid analysis and Display System (GrADS) soft-wares were used to process and display the results of the projected datasets of rainfall, Tmax and Tmin for the HS, NF and FF, respectively. The results show that the observed Tmax increased by the rates of 0.035℃ yr-1 and 0.0169℃ yr-1, while the Tmin was increased by a rate of 0.064℃ yr-1 and 0.104℃ yr-1 for Unguja and Pemba, respectively. The temporal distribution of wetness and dryness indices showed a climate shift from near normal to moderate wet during 2005 at Zanzibar Airport, while normal to moderately dry conditions, were observed in Pemba at Matangatuani. The decadal rainfall variability and distributions revealed higher rainfall intensity with an increasing trend and good spatial distribution in D3 from March to May (MAM) and October to December (OND). The projected results for Tmax during MAM and OND depicted higher values ranging from 1.7℃ - 1.8℃ to 1.9℃ - 2.0℃ and 1.5℃ to 2.0℃ in FF compared to NF under both RCPs. Also, higher Tmin values of 1.12℃ - 1.16℃ was projected in FF for MAM and OND under both RCPs. Besides, the rainfall projection generally revealed increased rainfall intensity in the range of 0 - 25 mm for Pemba and declined rainfall in the range of 25 - 50 mm in Unguja under both RCPs in perspectives of both NF and FF. Conclusively the study has shown that the undergoing climate change has posed a significant impact on both rainfall and temperature spatial and temporal distributions in Zanzibar (Unguja and Pemba), with Unguja being projected to have higher rainfall deficits while increasing rainfall strengths in Pemba. Thus, the study calls for more studies and formulation of effective adaptation, strategies and resilience mechanisms to combat the projected climate change impacts especially in the agricultural sector, water and food security.

Simulation of the spatio-temporal evolution of the electron energy distribution function in a pulsed hollow-cathode discharge

This article presents the 2D simulation results of a nanosecond pulsed hollow cathode discharge obtained through a combination of fluid and kinetic models.The spatio-temporal evolution of the electron energy distribution function(EEDF)of the plasma column and electrical characteristics of the nanosecond pulsed hollow cathode discharge at a gas pressure of 5 Torr are studied.The results show that the discharge development starts with the formation of an ionization front at the anode surface.The ionization front splits into two parts in the cathode cavity while propagating along its lateral surfaces.The ionization front formation leads to an increase in the fast isotropic EEDF component at its front,as well as in the anisotropic EEDF component.The accelerated electrons enter the cathode cavity,which significantly contributes to the formation of the highenergy EEDF component and EEDF anisotropy.

Spatial distribution of shallow landslides caused by Typhoon Lekima in 2019 in Zhejiang Province, China

In recent years, the coastal region of Southeast China has witnessed a significant increase in the frequency and intensity of extreme rainfall events associated with landfalling typhoons. The hilly and mountainous terrain of this area, combined with rapid rainfall accumulation, has led to a surge in flash floods and severe geological hazards. On August 10, 2019, Typhoon Lekima made landfall in Zhejiang Province, China, and its torrential rainfall triggered extensive landslides, resulting in substantial damage and economic losses. Utilizing high-resolution satellite images, we compiled a landslide inventory of the affected area, which comprises a total of 2,774 rainfallinduced landslides over an area of 2965 km2. The majority of these landslides were small to mediumsized and exhibited elongated, clustered patterns. Some landslides displayed characteristics of high-level initiation, obstructing or partially blocking rivers, leading to the formation of debris dams. We used the inventory to analyze the distribution pattern of the landslides and their relationship with topographical, geological, and hydrological factors. The results showed that landslide abundance was closely related to elevation, slope angle, faults, and road density. The landslides were predominantly located in hilly and low mountainous areas, with elevations ranging from 150 to 300 m, slopes of 20 to 30 degrees, and a NE-SE aspect. Notably, we observed the highest Landslide Number Density(LND) and Landslide Area Percentage(LAP) in the rhyolite region. Landslides were concentrated within approximately 4 km on either side of fault zones, with their size and frequency negatively correlated with distances to faults, roads, and river systems. Furthermore, under the influence of typhoons, regions with denser vegetation cover exhibited higher landslide density, reaching maximum values in shrubland areas. In areas experiencing significantly increased concentrated rainfall, landslide density also showed a corresponding rise. In terms of spatial distribution, the rainfall-triggered landslides primarily occurred in the northeastern part of the study area, particularly in regions characterized by complex topography such as Shanzao Village in Yantan Town, Xixia Township, and Shangzhang Township. The research findings offer crucial data on the rainfallinduced landslides triggered by Typhoon Lekima, shedding light on their spatial distribution patterns. These findings provide valuable references for mitigating risks and planning reconstruction in typhoon-affected area.

FPGA-based position reconstruction method for neutron beam flux spatial distribution measurement in BNCT

A new measurement method for the spatial distribution of neutron beam flux in boron neutron capture therapy(BNCT)is being developed based on the two-dimensional Micromegas detector.To address the issue of long processing times in traditional offline position reconstruction methods,this paper proposes a field programmable gate array based online position reconstruction method utilizing the micro-time projection chamber principle.This method encapsulates key technical aspects:a self-adaptive serial link technique built upon the dynamical adjustment of the delay chain length,fast sorting,a coordinate-matching technique based on the mapping between signal timestamps and random access memory(RAM)addresses,and a precise start point-merging technique utilizing a circular combined RAM.The performance test of the selfadaptive serial link shows that the bit error rate of the link is better than 10-12 at a confidence level of 99%,ensuring reliable data transmission.The experiment utilizing the readout electronics and Micromegas detector shows a spatial resolution of approximately 1.4 mm,surpassing the current method’s resolution level of 5 mm.The beam experiment confirms that the readout electronics system can obtain the flux spatial distribution of neutron beams online,thus validating the feasibility of the position reconstruction method.The online position reconstruction method avoids traditional methods,such as bubble sorting and traversal searching,simplifies the design of the logic firmware,and reduces the time complexity from O(n2)to O(n).This study contributes to the advancement in measuring neutron beam flux for BNCT.

Federated Learning Model for Auto Insurance Rate Setting Based on Tweedie Distribution

In the assessment of car insurance claims,the claim rate for car insurance presents a highly skewed probability distribution,which is typically modeled using Tweedie distribution.The traditional approach to obtaining the Tweedie regression model involves training on a centralized dataset,when the data is provided by multiple parties,training a privacy-preserving Tweedie regression model without exchanging raw data becomes a challenge.To address this issue,this study introduces a novel vertical federated learning-based Tweedie regression algorithm for multi-party auto insurance rate setting in data silos.The algorithm can keep sensitive data locally and uses privacy-preserving techniques to achieve intersection operations between the two parties holding the data.After determining which entities are shared,the participants train the model locally using the shared entity data to obtain the local generalized linear model intermediate parameters.The homomorphic encryption algorithms are introduced to interact with and update the model intermediate parameters to collaboratively complete the joint training of the car insurance rate-setting model.Performance tests on two publicly available datasets show that the proposed federated Tweedie regression algorithm can effectively generate Tweedie regression models that leverage the value of data fromboth partieswithout exchanging data.The assessment results of the scheme approach those of the Tweedie regressionmodel learned fromcentralized data,and outperformthe Tweedie regressionmodel learned independently by a single party.

Predicting the probability distribution of Martian rocks mechanical property based on microscale rock mechanical experiments and accurate grain-based modeling

The exploration of Mars would heavily rely on Martian rocks mechanics and engineering technology.As the mechanical property of Martian rocks is uncertain,it is of utmost importance to predict the probability distribution of Martian rocks mechanical property for the success of Mars exploration.In this paper,a fast and accurate probability distribution method for predicting the macroscale elastic modulus of Martian rocks was proposed by integrating the microscale rock mechanical experiments(micro-RME),accurate grain-based modeling(AGBM)and upscaling methods based on reliability principles.Firstly,the microstructure of NWA12564 Martian sample and elastic modulus of each mineral were obtained by micro-RME with TESCAN integrated mineral analyzer(TIMA)and nanoindentation.The best probability distribution function of the minerals was determined by Kolmogorov-Smirnov(K-S)test.Secondly,based on best distribution function of each mineral,the Monte Carlo simulations(MCS)and upscaling methods were implemented to obtain the probability distribution of upscaled elastic modulus.Thirdly,the correlation between the upscaled elastic modulus and macroscale elastic modulus obtained by AGBM was established.The accurate probability distribution of the macroscale elastic modulus was obtained by this correlation relationship.The proposed method can predict the probability distribution of Martian rocks mechanical property with any size and shape samples.