Spatio-temporal variation of water salinity in mangroves revealed by continuous monitoring and its relationship to floristic diversity

Salinity is among the most critical factors limiting the growth and species distribution of coastal plants.Water salinity in estuarine ecosystems varies temporally and spatially,but the variation patterns across different time scales and salinity fluctuation have rarely been quantified.The effects of salinity on floristic diversity in mangroves are not fully understood due to the temporal and spatial heterogeneity of salinity.In this study,we monitored water salinity at an interval of 10-min over one year in three mangrove catchment areas representing the outer part,middle part,and inner part respectively of Dongzhai Bay,Hainan,China.The number of mangrove community types and dominant mangrove species of the three catchment areas were also investigated.We found that the diurnal variation and dry-season intra-month variation in water salinity were driven by tidal cycles.The seasonal variation in water salinity was mainly driven by rainfall with higher salinity occurring in the dry season and lower salinity occurring in the wet season.Spatially,water salinity was highest at the outer part,intermediate at the middle part,and lowest at the inner part of the bay.The intra-month and annual fluctuations of water salinity were highest at the middle part and lowest at the outer part of the bay.The number of mangrove community types and dominant species were lowest at the outer part,intermediate at the middle part,and highest at the inner part of the bay.These results suggest that the temporal variation of water salinity in mangroves is driven by different factors at different time scales and therefore it is necessary to measure water salinity at different time scales to get a complete picture of the saline environment that mangroves experience.Spatially,lower salinity levels benefit mangrove species richness within a bay landscape,however,further research is needed to distinguish the effects of salinity fluctuation and salinity level in affecting mangrove species richness.

Resilience effects for household food expenditure and dietary diversity in rural western China

A more resilient livelihood is increasingly recognized as an efficient way to improve vulnerable households’food security and optimize their dietary decisions.This study quantifies rural household resilience in western China,identifies the three pillars(absorptive capacity,adaptive capacity,and transformative capacity)contribution to resilience,and then establishes the estimated Resilience Capacity Index(RCI)linked with food security and dietary diversity supported by the multiple indicator multiple cause(MIMIC)model.Results show that,despite geographical heterogeneity,the RCI consistently increased from 2015 to 2021.Households with a higher RCI inheriting better capacity to deal with risk and shocks are significantly and positively correlated with increasing food expenditure and diversifying food choices.It can be because resilient households will allocate more money to food expenditure instead of saving for livelihood uncertainty.Thus,policymakers can provide more incentives for rural households to adopt more dynamic and effective risk management strategies.This,in turn,could yield positive spillover effects by preventing human capital loss associated with dietary-related chronic diseases and mortality.

Off-farm employment,agriculture production activities,and household dietary diversity in environmentally and economically vulnerable areas of Asia

Access to off-farm employment has been expected to be a critical approach to ending hunger and all forms of malnutrition,two important targets of achieving Zero Hunger.This study aims to investigate the role of off-farm employment in improving dietary diversity through substitution effect and complementary effect with agricultural production activities and income effect.This study adopts Poisson/Tobit/Probit/OLS regressions and the instrument variable method based on the primary survey data collected among 1,282 households at 12 sites in environmentally and economically vulnerable areas of China,Nepal,Cambodia,Thailand,and Myanmar in 2019.The results show that off-farm employment is positively associated with household dietary diversity and the consumption of flesh meat,fish and other aquatic animals,fruits,and milk and dairy products,which are rich in protein and micronutrients.The results of mechanism analysis show that off-farm employment contributes to household dietary diversity by improving crop diversity,especially for poor households,boosting the probability of livestock raising for households with the middle one-third disposal income,and increasing household income.The positive association between off-farm employment and household dietary diversity is much higher for households with the bottom one-third disposal income,low illiteracy,and from upper-middle income countries.These findings imply that off-farm employment does play a vital role in achieving multiple benefits of poverty alleviation,malnutrition reduction,and agrobiodiversity conservation in environmentally and economically vulnerable areas.However,it may enlarge the gaps in dietary diversity between households with low human capital and from low and lower-middle income countries and those with high human capital and from middle-high countries.

Community structure and species diversity dynamics of a subtropical evergreen broad-leaved forest in China:2005 to 2020

Here,we characterize the temporal and spatial dynamics of forest community structure and species diversity in a subtropical evergreen broad-leaved forest in China.We found that community structure in this forest changed over a 15-year period.Specifically,renewal and death of common species was large,with the renewal of individuals mainly concentrated within a few populations,especially those of Aidia canthioides and Cryptocarya concinna.The numbers of individual deaths for common species were concentrated in the small and mid-diameter level.The spatial distribution of community species diversity fluctuated in each monitoring period,showing a more dispersed diversity after the 15-year study period,and the coefficient of variation on quadrats increased.In 2010,the death and renewal of the community and the spatial variation of species diversity were different compared to other survey years.Extreme weather may have affected species regeneration and community stability in our subtropical monsoon evergreen broad-leaved forests.Our findings suggest that strengthening the monitoring and management of the forest community will help better understand the long-and short-term causes of dynamic fluctuations of community structure and species diversity,and reveal the factors that drive changes in community structure.

Biodiversity metrics on ecological networks: Demonstrated with animal gastrointestinal microbiomes

Biodiversity has become a terminology familiar to virtually every citizen in modern societies.It is said that ecology studies the economy of nature,and economy studies the ecology of humans;then measuring biodiversity should be similar with measuring national wealth.Indeed,there have been many parallels between ecology and economics,actually beyond analogies.For example,arguably the second most widely used biodiversity metric,Simpson(1949)’s diversity index,is a function of familiar Gini-index in economics.One of the biggest challenges has been the high“diversity”of diversity indexes due to their excessive“speciation”-there are so many indexes,similar to each country’s sovereign currency-leaving confused diversity practitioners in dilemma.In 1973,Hill introduced the concept of“numbers equivalent”,which is based on Renyi entropy and originated in economics,but possibly due to his abstruse interpretation of the concept,his message was not widely received by ecologists until nearly four decades later.What Hill suggested was similar to link the US dollar to gold at the rate of$35 per ounce under the Bretton Woods system.The Hill numbers now are considered most appropriate biodiversity metrics system,unifying Shannon,Simpson and other diversity indexes.Here,we approach to another paradigmatic shift-measuring biodiversity on ecological networks-demonstrated with animal gastrointestinal microbiomes representing four major invertebrate classes and all six vertebrate classes.The network diversity can reveal the diversity of species interactions,which is a necessary step for understanding the spatial and temporal structures and dynamics of biodiversity across environmental gradients.

Biodiversity responses to insular fragmentation in Amazonia: Two decades of research in the Balbina Hydroelectric Reservoir

As hydropower development expands across lowland tropical forests,flooding and concomitant insular fragmentation have become important threats to biodiversity.Newly created insular landscapes serve as natural laboratories to investigate biodiversity responses to fragmentation.One of these most iconic landscapes is the Balbina Hydroelectric Reservoir in Brazilian Amazonia,occupying>400000 ha and comprising>3500 forest islands.Here,we synthesise the current knowledge on responses of a wide range of biological groups to insular fragmentation at Balbina.Sampling has largely concentrated on a set of 22 islands and three mainland sites.In total,39 studies were conducted over nearly two decades,covering 17 vertebrate,invertebrate,and plant taxa.Although species responses varied according to taxonomic group,island area was consistently included and played a pivotal role in 66.7%of all studies examining patterns of species diversity.Species persistence was further affected by species traits,mostly related to species capacity to use/traverse the aquatic matrix or tolerate habitat degradation,as noted for species of vertebrates and orchid bees.Further research is needed to improve our understanding of such effects on wider ecosystem functioning.Environmental Impact Assessments must account for changes in both the remaining habitat amount and configuration,and subsequent long-term species losses.

Strong evidence for latitudinal diversity gradient in mosses across the world

Species richness generally decreases with increasing latitude,a biodiversity gradient that has long been considered as one of the few laws in ecology.This latitudinal diversity gradient has been observed in many major groups of organisms.In plants,the latitudinal diversity gradient has been observed in vascular plants,angiosperms,ferns,and liverworts.However,a conspicuous latitudinal diversity gradient in mosses at a global or continental scale has not been observed until now.Here,we analyze a comprehensive data set including moss species in each band of 20° in latitude worldwide.Our results show that moss species richness decreases strongly with increasing latitude,regardless of whether the globe is considered as a whole or different longitudinal segments(e.g.,Old World versus New World) are considered separately.This result holds when variation in area size among latitudinal bands is taken into account.Pearson's correlation coefficient between latitude and species richness is-0.99 for both the Northern and Southern Hemispheres.Because bryophytes are an extant lineage of early land plants and because mosses not only include most of extant species of bryophytes but also are important constituents of most terrestrial ecosystems,understanding geographic patterns of mosses is particularly important The finding of our study fills a critical knowledge gap.

Diversity of Orchids in Terms of Their Distribution, Uses and Conservation in Annapurna Conservation Area of Nepal

The Annapurna Conservation Area (ACA), the first conservation area and the largest protected area (PA) in Nepal, is incredibly rich in biodiversity. Notwithstanding this, orchids in the ACA have not been explored enough yet thus making the need for ambitious research to be carried out. Previous study only included 81 species of orchids within ACA. This study aims to update the record of species and genera richness in the ACA. In total 198 species of orchids, belonging to 67 genera (40% and 62% of the total recorded orchid species and genera in Nepal) has been recorded in ACA. This represents an increase of 144% in species and 56% in genera over the previous data. Out of the 198 species, 99 were epiphytes, 6 were holomycotrophic and 93 were terrestrial. Among the 67 genera, Bulbophyllum (17) species were dominant, followed by Dendrobium (16), Herminium (10), Coelogyne, Plantanthera (9 each), Eria, Habenaria, Oberonia (8 each), Calanthe (7), and Liparis (6). Fifty-six species were found to be ornamentally significant and 85 species medicinally significant.

Genetic Diversity of Jute Mallow (Corchorus spp.) Accessions Based on ISSR Markers

Jute mallow is a nutritious leafy vegetable. The leaves are rich in proteins, vitamins and essential amino acids. Molecular characterization of Jute mallow with focus on improvement of leaf yield is scarcely reported. In the present study, inter sequence simple repeats (ISSR) molecular markers were employed to assess genetic diversity and relationships of 83 accessions of Jute mallow from different parts of Africa and Asia conserved at the World Vegetable Center East and Southern Africa. A total of 89 bands were amplified by 8 ISSR primers. Number of polymorphic bands per primer ranged from 2 to 6 with an average of 2.75 bands per primer. Polymorphic information content (PIC) values ranged from 0.390 to 0.760 with average of 0.53. Average Nei’s gene diversity (h) and Shannon’s information index (I) were 0.335 and 0.494 respectively. The highest pairwise genetic distance was 0.431 observed in a population from East Africa accessions. PC1 and PC2 axis explained 21.69% and 11.66% of the total variation respectively. UPGMA cluster analysis grouped the accessions into six main clusters at genetic similarity coefficient of 0.53 as standard value for classification. These results have important implications for jute mallow breeding and conservation.

Improved spatio-temporal alignment measurement method for hull deformation

In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial matching measurement of hull deformation under the coexistence of time delay and large misalignment angle.Large misalignment angle and time delay often occur simultaneously and bring great challenges to the accurate measurement of hull deformation in space and time.The proposed method utilizes coarse alignment with large misalignment angle and time delay estimation of inertial measurement unit modeling to establish a brand-new spatiotemporal aligned hull deformation measurement model.In addition,two-step loop control is designed to ensure the accurate description of dynamic deformation angle and static deformation angle by the time-space alignment method of hull deformation.The experiments illustrate that the proposed method can effectively measure the hull deformation angle when time delay and large misalignment angle coexist.

Epidemic Characteristics and Spatio-Temporal Patterns of HFRS in Qingdao City,China,2010-2022

Objective This study investigated the epidemic characteristics and spatio-temporal dynamics of hemorrhagic fever with renal syndrome(HFRS)in Qingdao City,China.Methods Information was collected on HFRS cases in Qingdao City from 2010 to 2022.Descriptive epidemiologic,seasonal decomposition,spatial autocorrelation,and spatio-temporal cluster analyses were performed.Results A total of 2,220 patients with HFRS were reported over the study period,with an average annual incidence of 1.89/100,000 and a case fatality rate of 2.52%.The male:female ratio was 2.8:1.75.3%of patients were aged between 16 and 60 years old,75.3%of patients were farmers,and 11.6%had both“three red”and“three pain”symptoms.The HFRS epidemic showed two-peak seasonality:the primary fall-winter peak and the minor spring peak.The HFRS epidemic presented highly spatially heterogeneous,street/township-level hot spots that were mostly distributed in Huangdao,Pingdu,and Jiaozhou.The spatio-temporal cluster analysis revealed three cluster areas in Qingdao City that were located in the south of Huangdao District during the fall-winter peak.Conclusion The distribution of HFRS in Qingdao exhibited periodic,seasonal,and regional characteristics,with high spatial clustering heterogeneity.The typical symptoms of“three red”and“three pain”in patients with HFRS were not obvious.

Genetic Diversity in Cowpea (Vigna unguiculata (L.) Walp) under Two Growing Conditions*

This study explores the use of genetic variability for advancing the genetic improvement of Cowpea (Vigna unguiculata (L.) Walp), particularly in response to insect infestation stress. Over a period spanning 2015 to 2017, forty accessions of cowpeas were evaluated to determine their variability under both insecticide spray and no insecticide spray conditions at the Teachings and Research Farms, Federal University of Agriculture, Abeokuta. The experimental design was a randomized complete block design in three replicates. The accessions were evaluated for plant height, leaf length, leaf width, number of days of 50% flowering, number of pods per plant, pod length, number of seeds per plant, 100-seed weight, and seed yield. Data collected were subjected to principal component and single linkage cluster analyses. Principal axis I (PCA1) accounted for 39% and 35% under insecticide spray and no insecticide spray respectively to the total variation in the accessions. Plant height with a factor score of 0.38, leaf length (0.41), number of leaves (0.37), and 100-seed, weight (0.30) was related to PCAI under insecticide spray while leaf width (0.32). Pod length (0.37) and number of seeds/plant (0.38) were significant to PCA1 under no insecticide spray. Notably, accessions such as SAMPEA6, SAMPEA10, IFE-Brown, and IFE-BPE exhibited consistent performance across both conditions, while others displayed condition-specific attributes. For instance, NGB1063, NGB1152, and NGB1093 demonstrated distinct traits under insecticide spray, while NGB1146 and NGB1124 exhibited notable characteristics under no insecticide spray conditions. Therefore, identifying these forty accessions with desirable traits hold promise for future genetic improvement efforts of cowpea cultivation in Nigeria and beyond.

Dynamic adaptive spatio-temporal graph network for COVID-19 forecasting

Appropriately characterising the mixed space-time relations of the contagion process caused by hybrid space and time factors remains the primary challenge in COVID-19 forecasting.However,in previous deep learning models for epidemic forecasting,spatial and temporal variations are captured separately.A unified model is developed to cover all spatio-temporal relations.However,this measure is insufficient for modelling the complex spatio-temporal relations of infectious disease transmission.A dynamic adaptive spatio-temporal graph network(DASTGN)is proposed based on attention mechanisms to improve prediction accuracy.In DASTGN,complex spatio-temporal relations are depicted by adaptively fusing the mixed space-time effects and dynamic space-time dependency structure.This dual-scale model considers the time-specific,space-specific,and direct effects of the propagation process at the fine-grained level.Furthermore,the model characterises impacts from various space-time neighbour blocks under time-varying interventions at the coarse-grained level.The performance comparisons on the three COVID-19 datasets reveal that DASTGN achieves state-of-the-art results with a maximum improvement of 17.092%in the root mean-square error and 11.563%in the mean absolute error.Experimental results indicate that the mechanisms of designing DASTGN can effectively detect some spreading characteristics of COVID-19.The spatio-temporal weight matrices learned in each proposed module reveal diffusion patterns in various scenarios.In conclusion,DASTGN has successfully captured the dynamic spatio-temporal variations of COVID-19,and considering multiple dynamic space-time relationships is essential in epidemic forecasting.

An Intelligent Framework for Resilience Recovery of FANETs with Spatio-Temporal Aggregation and Multi-Head Attention Mechanism

Due to the time-varying topology and possible disturbances in a conflict environment,it is still challenging to maintain the mission performance of flying Ad hoc networks(FANET),which limits the application of Unmanned Aerial Vehicle(UAV)swarms in harsh environments.This paper proposes an intelligent framework to quickly recover the cooperative coveragemission by aggregating the historical spatio-temporal network with the attention mechanism.The mission resilience metric is introduced in conjunction with connectivity and coverage status information to simplify the optimization model.A spatio-temporal node pooling method is proposed to ensure all node location features can be updated after destruction by capturing the temporal network structure.Combined with the corresponding Laplacian matrix as the hyperparameter,a recovery algorithm based on the multi-head attention graph network is designed to achieve rapid recovery.Simulation results showed that the proposed framework can facilitate rapid recovery of the connectivity and coverage more effectively compared to the existing studies.The results demonstrate that the average connectivity and coverage results is improved by 17.92%and 16.96%,respectively compared with the state-of-the-art model.Furthermore,by the ablation study,the contributions of each different improvement are compared.The proposed model can be used to support resilient network design for real-time mission execution.

Dietary Diversity and Food Security Status among Cameroonian Adults Living in Semi-Urban Areas: A Cross-Sectional Study

Introduction: Food security is one of the greatest challenges that most African countries face. It is a concept that considers not only food quantity but also food quality. The objective of this study was to describe dietary diversity and food security status at the individual level in Cameroonian populations. Methods: A total of 1180 men and women aged 20 and over and living in the West, North West, and Littoral regions of Cameroon were recruited. Data on dietary habits were collected through the frequency of consumption of various food groups. Dietary diversity was assessed using a 24-hour dietary recall. Food security status was determined by combining two indicators (food consumption score and individual food diversity score). Results: The mean dietary diversity score of the population was 3.53 ± 1.44, p Conclusion: The diet diversity of adults living in the West, North West, and Littoral regions of Cameroon is medium. Although half of the study population was food secure, there is a need to implement food security policies further to reduce food insecurity among the Cameroonian population.

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%.

Floristic Diversity, Stand Structure and Plant Life Traits in the Forest-Savanna Mosaic at Ndjole (Centre Cameroon)

With the aim of assessing floristic diversity, stand structure and vegetation ecology, the present work was carried out in the savanna mosaic forest of the locality of Ndjole (Centre Cameroon). A total of 30 floristic plots of 40 m × 40 m (1600 m2) were delineated in the different ecosystems (forest, forest-savanna contact zone and the savanna). Within each plot, all individuals with a diameter at breast height ≥ 10 cm at 1.30 m were taken into account. ANOVA was used to compare the means of the diversity indices of the different ecosystems, and the DUNCAN test at 5% significance level (XLSTAT 2016) to separate these means. A total of 85 species belonging to 67 genera and 33 families were recorded. That is, 68 species in semi-caducifolia forest, 45 in forest-savanna contact zone and 18 in savanna. Urticaceae, Combretaceae, Apocynaceae, Myristicaceae and Euphorbiaceae are the most diverse families in the forest. On the other hand, in contact zones, the Euphorbiaceae, Fabaceae, Annonaceae and Moraceae families are the most diversified, while in the savannas, the Combretaceae, Fabaceae and Annonaceae families are the most diversified. Shannon’s diversity index values (1.7 to 2.37 bits) reflect low specific diversity;Piélou’s equitability (0.86 to 0.9) shows good distribution of individuals within species. The diametric structure of woody species shows an inverted “J” shape in all plant communities. This indicates a high regeneration potential characterized by a greater number of small trees than large trees. Mesophanerophytes and megaphanerophytes are dominant in forests and forest-savanna contact zones, and microphanerophytes in the savannas. Endozoochory is the main mode of diaspore dissemination. As regards the distribution of phytogeographical types, it shows the overall dominance of Guineo-Congolese species in all plant communities. Our study provides detailed data on forest-savanna floristic and plant life traits in the mosaic and recommends further studies on the impact of environmental parameter variations on the forest encroachment into savanna.

Improving Diversity with Multi-Loss Adversarial Training in Personalized News Recommendation

Users’interests are often diverse and multi-grained,with their underlying intents even more so.Effectively captur-ing users’interests and uncovering the relationships between diverse interests are key to news recommendation.Meanwhile,diversity is an important metric for evaluating news recommendation algorithms,as users tend to reject excessive homogeneous information in their recommendation lists.However,recommendation models themselves lack diversity awareness,making it challenging to achieve a good balance between the accuracy and diversity of news recommendations.In this paper,we propose a news recommendation algorithm that achieves good performance in both accuracy and diversity.Unlike most existing works that solely optimize accuracy or employ more features to meet diversity,the proposed algorithm leverages the diversity-aware capability of the model.First,we introduce an augmented user model to fully capture user intent and the behavioral guidance they might undergo as a result.Specifically,we focus on the relationship between the original clicked news and the augmented clicked news.Moreover,we propose an effective adversarial training method for diversity(AT4D),which is a pluggable component that can enhance both the accuracy and diversity of news recommendation results.Extensive experiments on real-world datasets confirm the efficacy of the proposed algorithm in improving both the accuracy and diversity of news recommendations.

A cloud model target damage effectiveness assessment algorithm based on spatio-temporal sequence finite multilayer fragments dispersion

To solve the problem of target damage assessment when fragments attack target under uncertain projectile and target intersection in an air defense intercept,this paper proposes a method for calculating target damage probability leveraging spatio-temporal finite multilayer fragments distribution and the target damage assessment algorithm based on cloud model theory.Drawing on the spatial dispersion characteristics of fragments of projectile proximity explosion,we divide into a finite number of fragments distribution planes based on the time series in space,set up a fragment layer dispersion model grounded in the time series and intersection criterion for determining the effective penetration of each layer of fragments into the target.Building on the precondition that the multilayer fragments of the time series effectively assail the target,we also establish the damage criterion of the perforation and penetration damage and deduce the damage probability calculation model.Taking the damage probability of the fragment layer in the spatio-temporal sequence to the target as the input state variable,we introduce cloud model theory to research the target damage assessment method.Combining the equivalent simulation experiment,the scientific and rational nature of the proposed method were validated through quantitative calculations and comparative analysis.

Self-Attention Spatio-Temporal Deep Collaborative Network for Robust FDIA Detection in Smart Grids

False data injection attack(FDIA)can affect the state estimation of the power grid by tampering with the measured value of the power grid data,and then destroying the stable operation of the smart grid.Existing work usually trains a detection model by fusing the data-driven features from diverse power data streams.Data-driven features,however,cannot effectively capture the differences between noisy data and attack samples.As a result,slight noise disturbances in the power grid may cause a large number of false detections for FDIA attacks.To address this problem,this paper designs a deep collaborative self-attention network to achieve robust FDIA detection,in which the spatio-temporal features of cascaded FDIA attacks are fully integrated.Firstly,a high-order Chebyshev polynomials-based graph convolution module is designed to effectively aggregate the spatio information between grid nodes,and the spatial self-attention mechanism is involved to dynamically assign attention weights to each node,which guides the network to pay more attention to the node information that is conducive to FDIA detection.Furthermore,the bi-directional Long Short-Term Memory(LSTM)network is introduced to conduct time series modeling and long-term dependence analysis for power grid data and utilizes the temporal selfattention mechanism to describe the time correlation of data and assign different weights to different time steps.Our designed deep collaborative network can effectively mine subtle perturbations from spatiotemporal feature information,efficiently distinguish power grid noise from FDIA attacks,and adapt to diverse attack intensities.Extensive experiments demonstrate that our method can obtain an efficient detection performance over actual load data from New York Independent System Operator(NYISO)in IEEE 14,IEEE 39,and IEEE 118 bus systems,and outperforms state-of-the-art FDIA detection schemes in terms of detection accuracy and robustness.