Secure Wireless Communication via Movable-Antenna Array

Movable antenna (MA) array is a novel technology recently developed where positions of transmit/receive antennas can be flexibly adjusted in the specified region to reconfigure the wireless channel and achieve a higher capacity. In this letter, we, for the first time, investigate the MA array-assisted physical-layer security where the confidential information is transmitted from a MA array-enabled Alice to a single-antenna Bob, in the presence of multiple single-antenna and colluding eavesdroppers. We aim to maximize the achievable secrecy rate by jointly designing the transmit beamforming and positions of all antennas at Alice subject to the transmit power budget and specified regions for positions of all transmit antennas. The resulting problem is highly non-convex, for which the projected gradient ascent (PGA) and the alternating optimization methods are utilized to obtain a high-quality suboptimal solution. Simulation results demonstrate that since the additional spatial degree of freedom (DoF) can be fully exploited, the MA array significantly enhances the secrecy rate compared to the conventional fixed-position antenna (FPA) array

Time2Graph: Revisiting Time Series Modeling with Dynamic Shapelets

Time series modeling has attracted extensive research efforts; however, achieving both reliable efficiency and interpretability from a unified model still remains a challenging problem. Among the literature, shapelets offer interpretable and explanatory insights in the classification tasks, while most existing works ignore the differing representative power at different time slices, as well as (more importantly) the evolution pattern of shapelets. In this paper, we propose to extract time-aware shapelets by designing a two-level timing factor. Moreover, we define and construct the shapelet evolution graph, which captures how shapelets evolve over time and can be incorporated into the time series embeddings by graph embedding algorithms. To validate whether the representations obtained in this way can be applied effectively in various scenarios, we conduct experiments based on three public time series datasets, and two real-world datasets from different domains. Experimental results clearly show the improvements achieved by our approach compared with 17 state-of-the-art baselines.Comment: An extended version with 11 pages including appendix; Accepted by AAAI'202

Simultaneous utilization of glucose and xylose for lipid production by Trichosporon cutaneum

<p>Abstract</p> <p>Background</p> <p>Biochemical conversion of lignocellulose hydrolysates remains challenging, largely because most microbial processes have markedly reduced efficiency in the presence of both hexoses and pentoses. Thus, identification of microorganisms capable of efficient and simultaneous utilization of both glucose and xylose is pivotal to improving this process.</p> <p>Results</p> <p>In this study, we found that the oleaginous yeast strain <it>Trichosporon cutaneum </it>AS 2.571 assimilated glucose and xylose simultaneously, and accumulated intracellular lipid up to 59 wt% with a lipid coefficient up to 0.17 g/g sugar, upon cultivation on a 2:1 glucose/xylose mixture in a 3-liter stirred-tank bioreactor. In addition, no classic pattern of diauxic growth behavior was seen; the microbial cell mass increased during the whole culture process without any lag periods. In shake-flask cultures with different initial glucose:xylose ratios, glucose and xylose were consumed simultaneously at rates roughly proportional to their individual concentrations in the medium, leading to complete utilization of both sugars at the same time. Simultaneous utilization of glucose and xylose was also seen during fermentation of corn-stover hydrolysate with a lipid content and coefficient of 39.2% and 0.15 g/g sugar, respectively. The lipid produced had a fatty-acid compositional profile similar to those of conventional vegetable oil, indicating that it could have potential as a raw material for biodiesel production.</p> <p>Conclusion</p> <p>Efficient lipid production with simultaneous consumption of glucose and xylose was achieved in this study. This process provides an exciting opportunity to transform lignocellulosic materials into biofuel molecules, and should also encourage further study to elucidate this unique sugar-assimilation mechanism.</p

The functional implications of Termitomyces domestication on fungus-growing termite gut microbiomes

Patients with chronic or recurrent otitis media with effusion who do not respond to treatment with conventional ventilation tubes are often treated with long-term ventilation tubes. The aim of this retrospective study was to determine the extrusion and complication rates of long-term ventilation tubes. The median ventilation time of the tubes was 31.5 months. The most common complication was otorrhoea. One episode of otorrhoea occurred after 24% of all tube insertions, and recurrent otorrhoea occurred in 29%. A persisting perforation developed in 19% after extrusion or removal of the tube. Other, mostly minor, complications occurred in 36% with the tube in situ and in 3% after extrusion or removal of the tube. Long-term ventilation tubes provided prolonged ventilation of the middle ear, but also resulted in a considerable number of complications. For each individual case, one should therefore determine whether the advantages of long-term ventilation tubes outweigh the possible complications in view of the available alternatives for middle ear ventilation

Deep air learning: Interpolation, prediction, and feature analysis of fine-grained air quality

The interpolation, prediction, and feature analysis of fine-gained air quality are three important topics in the area of urban air computing. The solutions to these topics can provide extremely useful information to support air pollution control, and consequently generate great societal and technical impacts. Most of the existing work solves the three problems separately by different models. In this paper, we propose a general and effective approach to solve the three problems in one model called the Deep Air Learning (DAL). The main idea of DAL lies in embedding feature selection and semi-supervised learning in different layers of the deep learning network. The proposed approach utilizes the information pertaining to the unlabeled spatio-temporal data to improve the performance of the interpolation and the prediction, and performs feature selection and association analysis to reveal the main relevant features to the variation of the air quality. We evaluate our approach with extensive experiments based on real data sources obtained in Beijing, China. Experiments show that DAL is superior to the peer models from the recent literature when solving the topics of interpolation, prediction, and feature analysis of fine-gained air quality

Deciphering the role of rapidly evolving conserved elements in primate brain development and exploring their potential involvement in Alzheimer's Disease

Although previous studies have identified human-specific accelerated regions as playing a key role in the recent evolution of the human brain, the characteristics and cellular functions of rapidly evolving conserved elements (RECEs) in ancestral primate lineages remain largely unexplored. Here, based on large-scale primate genome assemblies, we identify 888 RECEs that have been highly conserved in primates that exhibit significantly accelerated substitution rates in the ancestor of the Simiiformes. This primate lineage exhibits remarkable morphological innovations, including an expanded brain mass. Integrative multiomic analyses reveal that RECEs harbor sequences with potential cis-regulatory functions that are activated in the adult human brain. Importantly, genes linked to RECEs exhibit pronounced expression trajectories in the adult brain relative to the fetal stage. Furthermore, we observed an increase in the chromatin accessibility of RECEs in oligodendrocytes from individuals with Alzheimer's disease (AD) compared to that of a control group, indicating that these RECEs may contribute to brain aging and AD. Our findings serve to expand our knowledge of the genetic underpinnings of brain function during primate evolution

Epigenetic modification and inheritance in sexual reversal of fish

Environmental sex determination (ESD) occurs in divergent, phylogenetically unrelated taxa, and in some species, co-occurs with genetic sex determination (GSD) mechanisms. Although epigenetic regulation in response to environmental effects has long been proposed to be associated with ESD, a systemic analysis on epigenetic regulation of ESD is still lacking. Using half-smooth tongue sole (Cynoglossus semilaevis) as a model—a marine fish that has both ZW chromosomal GSD and temperature-dependent ESD—we investigated the role of DNA methylation in transition from GSD to ESD. Comparative analysis of the gonadal DNA methylomes of pseudomale, female, and normal male fish revealed that genes in the sex determination pathways are the major targets of substantial methylation modification during sexual reversal. Methylation modification in pseudomales is globally inherited in their ZW offspring, which can naturally develop into pseudomales without temperature incubation. Transcriptome analysis revealed that dosage compensation occurs in a restricted, methylated cytosine enriched Z chromosomal region in pseudomale testes, achieving equal expression level in normal male testes. In contrast, female-specific W chromosomal genes are suppressed in pseudomales by methylation regulation. We conclude that epigenetic regulation plays multiple crucial roles in sexual reversal of tongue sole fish. We also offer the first clues on the mechanisms behind gene dosage balancing in an organism that undergoes sexual reversal. Finally, we suggest a causal link between the bias sex chromosome assortment in the offspring of a pseudomale family and the transgenerational epigenetic inheritance of sexual reversal in tongue sole fish

Reciprocal genomic evolution in the ant-fungus agricultural symbiosis

The attine ant–fungus agricultural symbiosis evolved over tens of millions of years, producing complex societies with industrial-scale farming analogous to that of humans. Here we document reciprocal shifts in the genomes and transcriptomes of seven fungus-farming ant species and their fungal cultivars. We show that ant subsistence farming probably originated in the early Tertiary (55–60 MYA), followed by further transitions to the farming of fully domesticated cultivars and leaf-cutting, both arising earlier than previously estimated. Evolutionary modifications in the ants include unprecedented rates of genome-wide structural rearrangement, early loss of arginine biosynthesis and positive selection on chitinase pathways. Modifications of fungal cultivars include loss of a key ligninase domain, changes in chitin synthesis and a reduction in carbohydrate-degrading enzymes as the ants gradually transitioned to functional herbivory. In contrast to human farming, increasing dependence on a single cultivar lineage appears to have been essential to the origin of industrial-scale ant agriculture