Robust Transmissions in Wireless Powered Multi-Relay Networks with Chance Interference Constraints

In this paper, we consider a wireless powered multi-relay network in which a multi-antenna hybrid access point underlaying a cellular system transmits information to distant receivers. Multiple relays capable of energy harvesting are deployed in the network to assist the information transmission. The hybrid access point can wirelessly supply energy to the relays, achieving multi-user gains from signal and energy cooperation. We propose a joint optimization for signal beamforming of the hybrid access point as well as wireless energy harvesting and collaborative beamforming strategies of the relays. The objective is to maximize network throughput subject to probabilistic interference constraints at the cellular user equipment. We formulate the throughput maximization with both the time-switching and power-splitting schemes, which impose very different couplings between the operating parameters for wireless power and information transfer. Although the optimization problems are inherently non-convex, they share similar structural properties that can be leveraged for efficient algorithm design. In particular, by exploiting monotonicity in the throughput, we maximize it iteratively via customized polyblock approximation with reduced complexity. The numerical results show that the proposed algorithms can achieve close to optimal performance in terms of the energy efficiency and throughput.Comment: 14 pages, 8 figure

Capacity Constrained Influence Maximization in Social Networks

Influence maximization (IM) aims to identify a small number of influential individuals to maximize the information spread and finds applications in various fields. It was first introduced in the context of viral marketing, where a company pays a few influencers to promote the product. However, apart from the cost factor, the capacity of individuals to consume content poses challenges for implementing IM in real-world scenarios. For example, players on online gaming platforms can only interact with a limited number of friends. In addition, we observe that in these scenarios, (i) the initial adopters of promotion are likely to be the friends of influencers rather than the influencers themselves, and (ii) existing IM solutions produce sub-par results with high computational demands. Motivated by these observations, we propose a new IM variant called capacity constrained influence maximization (CIM), which aims to select a limited number of influential friends for each initial adopter such that the promotion can reach more users. To solve CIM effectively, we design two greedy algorithms, MG-Greedy and RR-Greedy, ensuring the $1/2$-approximation ratio. To improve the efficiency, we devise the scalable implementation named RR-OPIM+ with $(1/2-\epsilon)$-approximation and near-linear running time. We extensively evaluate the performance of 9 approaches on 6 real-world networks, and our solutions outperform all competitors in terms of result quality and running time. Additionally, we deploy RR-OPIM+ to online game scenarios, which improves the baseline considerably.Comment: The technical report of the paper entitled 'Capacity Constrained Influence Maximization in Social Networks' in SIGKDD'2

Missing call bias in high-throughput genotyping

© 2009 Fu et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

DiffCloth: Diffusion Based Garment Synthesis and Manipulation via Structural Cross-modal Semantic Alignment

Cross-modal garment synthesis and manipulation will significantly benefit the way fashion designers generate garments and modify their designs via flexible linguistic interfaces.Current approaches follow the general text-to-image paradigm and mine cross-modal relations via simple cross-attention modules, neglecting the structural correspondence between visual and textual representations in the fashion design domain. In this work, we instead introduce DiffCloth, a diffusion-based pipeline for cross-modal garment synthesis and manipulation, which empowers diffusion models with flexible compositionality in the fashion domain by structurally aligning the cross-modal semantics. Specifically, we formulate the part-level cross-modal alignment as a bipartite matching problem between the linguistic Attribute-Phrases (AP) and the visual garment parts which are obtained via constituency parsing and semantic segmentation, respectively. To mitigate the issue of attribute confusion, we further propose a semantic-bundled cross-attention to preserve the spatial structure similarities between the attention maps of attribute adjectives and part nouns in each AP. Moreover, DiffCloth allows for manipulation of the generated results by simply replacing APs in the text prompts. The manipulation-irrelevant regions are recognized by blended masks obtained from the bundled attention maps of the APs and kept unchanged. Extensive experiments on the CM-Fashion benchmark demonstrate that DiffCloth both yields state-of-the-art garment synthesis results by leveraging the inherent structural information and supports flexible manipulation with region consistency.Comment: accepted by ICCV202

Large‐scale changes in macrobenthic biodiversity driven by mangrove afforestation

1. Large- scale anthropogenic mangroves have been constructed in coastal regions worldwide but our understanding of their ecological effects is limited. In particu-lar, the question of whether and how anthropogenic mangroves influence biodi-versity patterns remains elusive.2. Here, we investigated the influence of large-scale anthropogenic mangroves on biodiversity patterns of mangrove macrobenthos. Specifically, we measure and seek to explain differences in species richness, abundance, assemblage composi-tion and distance-decay effect before and after the construction of anthropo-genic mangroves.3. We surveyed assemblages of gastropod, bivalve and crab species over a wide latitudinal extent (24–28°N) in subtropical China. For each, we calculated species richness, abundance, assemblage composition and distance-decay relationship before and after the construction of anthropogenic mangroves.4. After the large-scale anthropogenic mangroves, we found species richness of gas-tropods, bivalves and crabs increased by 23.81%, 100% and 20%, respectively. The distance-decay effects of gastropods and bivalves decreased by 25% and 91.43%, while that of crabs remained virtually unchanged, which mediated by in-creased dispersal rate of macrobenthos. With mangrove plantation, compositional similarity of crab and bivalve assemblages increased by 28.57% and 38.46%, sug-gesting that large-scale monospecific planting exacerbate biotic homogenization. Altogether, these results indicate that large-scale anthropogenic habitats increase the diversity of mangrove macrobenthos and change taxonomic compositions by reducing distance-decay effects and increasing dispersal rate of macrobenthos.5. Synthesis and applications. We emphasize that afforestation of coastal wetlands can drive major changes in benthonic communities. Monitoring and assessing the ecological effects of the anthropogenic habitats for the presence of functional faunas will be important in determining the future coastal restoration and main-taining economic aquaculture. Quantifying those effects in terms of regional bio-diversity composition will contribute to the management of coastal restoration to be based upon macroevidence rather than a one-sided local perspective.info:eu-repo/semantics/publishedVersio