Study of Wind Flow Angle and Velocity on Ice Accretion of Transmission Line Composite Insulators

Ice accretion on insulators in cold regions is a serious and inevitable problem for power transmission lines, which may cause over-load and icing flashover accidents and can lead to wide power outage. In this research work, multiphase numerical simulations are carried out to investigate the effect of wind flow angle & velocity on the ice accretion of transmission line composite insulators. To verify the simulation results, lab-based icing tests are carried out in artificial climate chamber of Chongqing University. Results show that the change of wind flow angle has an obvious effect on both accreted ice shape and ice mass of insulators. When wind flow angle changes from 0° to 90° or -90°, the ice mass increases before dropping sharply. Meanwhile, ice mass accretion on insulators with wind flow angle is more sensitive to the change of wind velocity. For V-shape insulator strings, the ice mass increased 47.22% in average compared to ordinary suspension insulators. The findings of this research can provide significant engineering reference for the design of transmission line in icing prone areas

A Survey on Federated Unlearning: Challenges, Methods, and Future Directions

In recent years, the notion of ``the right to be forgotten" (RTBF) has evolved into a fundamental element of data privacy regulations, affording individuals the ability to request the removal of their personal data from digital records. Consequently, given the extensive adoption of data-intensive machine learning (ML) algorithms and increasing concerns for personal data privacy protection, the concept of machine unlearning (MU) has gained considerable attention. MU empowers an ML model to selectively eliminate sensitive or personally identifiable information it acquired during the training process. Evolving from the foundational principles of MU, federated unlearning (FU) has emerged to confront the challenge of data erasure within the domain of federated learning (FL) settings. This empowers the FL model to unlearn an FL client or identifiable information pertaining to the client while preserving the integrity of the decentralized learning process. Nevertheless, unlike traditional MU, the distinctive attributes of federated learning introduce specific challenges for FU techniques. These challenges lead to the need for tailored design when designing FU algorithms. Therefore, this comprehensive survey delves into the techniques, methodologies, and recent advancements in federated unlearning. It provides an overview of fundamental concepts and principles, evaluates existing federated unlearning algorithms, reviews optimizations tailored to federated learning, engages in discussions regarding practical applications, along with an assessment of their limitations, and outlines promising directions for future research

CSPM: A Contrastive Spatiotemporal Preference Model for CTR Prediction in On-Demand Food Delivery Services

Click-through rate (CTR) prediction is a crucial task in the context of an online on-demand food delivery (OFD) platform for precisely estimating the probability of a user clicking on food items. Unlike universal e-commerce platforms such as Taobao and Amazon, user behaviors and interests on the OFD platform are more location and time-sensitive due to limited delivery ranges and regional commodity supplies. However, existing CTR prediction algorithms in OFD scenarios concentrate on capturing interest from historical behavior sequences, which fails to effectively model the complex spatiotemporal information within features, leading to poor performance. To address this challenge, this paper introduces the Contrastive Sres under different search states using three modules: contrastive spatiotemporal representation learning (CSRL), spatiotemporal preference extractor (StPE), and spatiotemporal information filter (StIF). CSRL utilizes a contrastive learning framework to generate a spatiotemporal activation representation (SAR) for the search action. StPE employs SAR to activate users' diverse preferences related to location and time from the historical behavior sequence field, using a multi-head attention mechanism. StIF incorporates SAR into a gating network to automatically capture important features with latent spatiotemporal effects. Extensive experiments conducted on two large-scale industrial datasets demonstrate the state-of-the-art performance of CSPM. Notably, CSPM has been successfully deployed in Alibaba's online OFD platform Ele.me, resulting in a significant 0.88% lift in CTR, which has substantial business implications

Multiple facets of stream macroinvertebrate alpha diversity are driven by different ecological factors across an extensive altitudinal gradient

Environmental filtering and spatial structuring are important ecological processes for the generation and maintenance of biodiversity. However, the relative importance of these ecological drivers for multiple facets of diversity is still poorly understood in highland streams. Here, we examined the responses of three facets of stream macroinvertebrate alpha diversity to local environmental, landscape-climate and spatial factors in a near-pristine highland riverine ecosystem. Taxonomic (species richness, Shannon diversity, and evenness), functional (functional richness, evenness, divergence, and Rao's Quadratic entropy), and a proxy of phylogenetic alpha diversity (taxonomic distinctness and variation in taxonomic distinctness) were calculated for macroinvertebrate assemblages in 55 stream sites. Then Pearson correlation coefficient was used to explore congruence of indices within and across the three diversity facets. Finally, multiple linear regression models and variation partitioning were employed to identify the relative importance of different ecological drivers of biodiversity. We found most correlations between the diversity indices within the same facet, and between functional richness and species richness were relatively strong. The two phylogenetic diversity indices were quite independent from taxonomic diversity but correlated with functional diversity indices to some extent. Taxonomic and functional diversity were more strongly determined by environmental variables, while phylogenetic diversity was better explained by spatial factors. In terms of environmental variables, habitat-scale variables describing habitat complexity and water physical features played the primary role in determining the diversity patterns of all three facets, whereas landscape factors appeared less influential. Our findings indicated that both environmental and spatial factors are important ecological drivers for biodiversity patterns of macroinvertebrates in Tibetan streams, although their relative importance was contingent on different facets of diversity. Such findings verified the complementary roles of taxonomic, functional and phylogenetic diversity, and highlighted the importance of comprehensively considering multiple ecological drivers for different facets of diversity in biodiversity assessment

Different responses of taxonomic and functional structures of stream macroinvertebrate communities to local stressors and regional factors in a subtropical biodiversity hotspot

Post-print version of the article Publisher's version/doi: 10.1016/j.scitotenv.2018.11.222Examining the relative contribution of local environmental stressors and regional factors in structuring biological communities is essential for biodiversity conservation and environmental assessment, yet their relative roles for different community characterizations remain elusive. Here, we examined the responses of taxonomic and functional structures of stream macroinvertebrate communities to local and regional factors across a human-induced environmental gradient in the Han River Basin, one subtropical biodiversity hotspot in China. Our objectives were: 1) to examine the responses of traditional taxonomic measures and functional traits to anthropogenic disturbances; 2) to compare the relative importance of environmental versus spatial variables and catchment-scale versus reach-scale variables for the two community characterizations. We found that both species and trait compositions performed well in differentiating anthropogenic disturbances, indicating that both taxonomic and functional structures of macroinvertebrate communities were strongly altered by human activities. Particularly, some traits related to life history (e.g., voltinism), resilience and resistance (e.g., adult flying ability) are well suited for predicting changes of communities towards anthropogenic disturbances owing to their mechanistic relationship with environmental gradients. We found that environmental variables played more important roles than spatial effects in structuring both taxonomic and functional facets of macroinvertebrate communities. Environmental filtering was more important in determining functional than taxonomic structure, and the opposite was true for spatial effects. In terms of environmental variables, catchment land-uses played the primary role in determining taxonomic composition, whereas reach-scale variables related to local habitat heterogeneity were more influential for functional structure. Our study highlights the importance of employing metacommunity perspectives and different community characterizations in both theoretical and applied research. For stream bioassessment and management, we argue that the combination of taxonomic and functional characterizations of community should be implemented, as different facets of biological communities responded to different types of anthropogenic disturbances

Disentangling the effects of dispersal mode on the assembly of macroinvertebrate assemblages in a heterogeneous highland region

Disentangling the effects of dispersal mode on the environmental and spatial processes structuring biological assemblages is essential to understanding the mechanisms of species coexistence and maintenance. Here, we use field investigations to link dispersal mode with environmental and spatial processes that control stream macroinvertebrate assemblage structure across the Yarlung Zangbo Grand Canyon of Tibet (Tibetan Plateau). We sampled macroinvertebrates in streams that occur in 4 distinct regions. Each of these regions has a steep elevational gradient but different altitude ranges, climate types, and water replenishment sources. We classified macroinvertebrate taxa into passive and active dispersal mode groups to test whether macroinvertebrates with different dispersal modes responded differently to environmental and spatial processes. Our results showed that the assemblage structure of active dispersal groups was more strongly determined by environmental variables (habitat filtering/species sorting) than spatial factors both within and across regions. In contrast, the structure of passive dispersers was more strongly associated with spatial factors than environmental filtering in the entire study area and within lower canyon regions. However, spatial effects were not important for either type of dispersal group in the upper canyon regions, especially in the region with glacier-fed streams, indicating the predominance of species sorting processes in these harsh environments. Furthermore, the spatial structuring of assemblages became stronger as habitat filtering declined, which indicates a reduction in species sorting processes in less harsh environments. Our findings demonstrate diverse responses of macroinvertebrate assemblages to environmental and spatial processes across this poorly-known highland river system, and imply that dispersal mode influences the underlying mechanisms of community variation

Understanding macroinvertebrate metacommunity organization using a nested study design across a mountainous river network

Metacommunity ecology highlights the importance of integrating simultaneously environmental filtering and spatial processes, such as mass effects and dispersal limitation, into investigation of community assembly. However, few studies to date have tried to examine mass effects and dispersal limitation as independent ecological mechanisms along with environmental filtering in shaping biological communities in river networks. We examined the relative importance of three factor groups, i.e., environmental variables, within-river spatial factors (indicative of mass effects) and basin identity (referring to dispersal limitation) on a macroinvertebrate metacommunity and nine trait-based deconstructed sub-metacommunities from seven subtropical rivers. We applied redundancy analysis and variance partitioning to reveal the pure and shared effects of the three groups of factors on community variation. Environmental filtering, mass effects and dispersal limitation were all significant mechanisms affecting variation in macroinvertebrate communities, but their relative importance depended on biological traits. Environmental filtering explained more of the variation in the whole metacommunity, tolerant taxa and macroinvertebrate groups with weak dispersal ability (i.e., aquatic dispersal, aerial passive dispersal and large body size). In contrast, mass effects accounted for more variation in the communities of intolerant taxa and macroinvertebrate groups with strong dispersal ability (i.e., aerial active dispersal mode and medium body size). Dispersal limitation was more influential for sub-communities of moderately tolerant taxa and large-sized taxa. Our study highlights that simultaneously accounting for different spatial processes and using a trait-based approach are essential to improve our understanding of community assembly in river networks

New insights into the germline genes and CDR3 repertoire of the TCRβ chain in Chiroptera

IntroductionBats are recognized as natural reservoirs for many viruses, and their unique immune system enables them to coexist with these viruses without frequently exhibiting disease symptoms. However, the current understanding of the bat adaptive immune system is limited due to the lack of a database or tool capable of processing T-cell receptor (TCR) sequences for bats.MethodsWe performed germline gene annotation in three bat species using homologous genes and RSSs (Recombinational Signal Sequences) scanning method. Then we used the conserved C gene to construct the TCRβ chain receptor library of the Intermediate Horseshoe Bat. Bats' TCRβ data will be analyzed using MiXCR and constructed reference library.ResultsRegarding the annotation results, we found that the Pale Spear-nosed Bat has 37 members in the TRBV12 family, which is more than the total number of TRBV genes in the Greater Horseshoe Bat. The average number of unique TCRβ chain receptor sequences in each Intermediate Horseshoe Bat sample reached 24,904.DiscussionThe distinct variations in the distribution of TRBV genes among the three types of bats could have a direct impact on the diversity of the TCR repertoire, as evidenced by the presence of conserved amino acids that indicate the T-cell recognition of antigens in bats is MHC-restricted. The bats’ TCRβ repertoire is formed through the rearrangement of the V-D-J-C genes, with D-J/V-D deletions and insertions resulting in high diversity

Unimodal productivity-biodiversity relationship along the gradient of multidimensional resources across Chinese grasslands

Resources can affect plant productivity and biodiversity simultaneously and thus are key drivers of their relationships in addition to plant-plant interactions. However, most previous studies only focused on a single resource while neglecting the nature of resource multidimensionality. Here we integrated four essential resources for plant growth into a single metric of resource diversity (RD) to investigate its effects on the productivity-biodiversity relationship (PBR) across Chinese grasslands. Results showed that habitats differing in RD have different PBRs − positive in low-resource habitats, but neutral in medium- and high-resource ones—while collectively, a weak positive PBR was observed. However, when excluding direct effects of RD on productivity and biodiversity, PBR in high-resource habitats became negative, which leads to a unimodal instead of a positive PBR along the RD gradient. By integrating resource effects and changing plant-plant interactions into a unified framework with the RD gradient, our work contributes to uncovering underlying mechanisms for inconsistent PBRs at large scales