Existence and controllability for stochastic evolution inclusions of Clarke's subdifferential type

In this paper, we investigate a class of stochastic evolution inclusions of Clarke's subdifferential type in Hilbert spaces. The existence of mild solutions and controllability results are given and proved by using stochastic analysis techniques, semigroup of operators theory, a fixed point theorem of multivalued maps and properties of generalized Clarke subdifferential. An example is included to illustrate the applicability of the main results

Force-Aware Interface via Electromyography for Natural VR/AR Interaction

While tremendous advances in visual and auditory realism have been made for virtual and augmented reality (VR/AR), introducing a plausible sense of physicality into the virtual world remains challenging. Closing the gap between real-world physicality and immersive virtual experience requires a closed interaction loop: applying user-exerted physical forces to the virtual environment and generating haptic sensations back to the users. However, existing VR/AR solutions either completely ignore the force inputs from the users or rely on obtrusive sensing devices that compromise user experience. By identifying users' muscle activation patterns while engaging in VR/AR, we design a learning-based neural interface for natural and intuitive force inputs. Specifically, we show that lightweight electromyography sensors, resting non-invasively on users' forearm skin, inform and establish a robust understanding of their complex hand activities. Fuelled by a neural-network-based model, our interface can decode finger-wise forces in real-time with 3.3% mean error, and generalize to new users with little calibration. Through an interactive psychophysical study, we show that human perception of virtual objects' physical properties, such as stiffness, can be significantly enhanced by our interface. We further demonstrate that our interface enables ubiquitous control via finger tapping. Ultimately, we envision our findings to push forward research towards more realistic physicality in future VR/AR.Comment: ACM Transactions on Graphics (SIGGRAPH Asia 2022

Transcriptional regulator-mediated activation of adaptation genes triggers CRISPR <i>de novo</i> spacer acquisition

Acquisition of de novo spacer sequences confers CRISPR-Cas with a memory to defend against invading genetic elements. However, the mechanism of regulation of CRISPR spacer acquisition remains unknown. Here we examine the transcriptional regulation of the conserved spacer acquisition genes in Type I-A of Sulfolobus islandicus REY15A. Csa3a, a MarR-like transcription factor encoded by the gene located adjacent to csa1, cas1, cas2 and cas4 cluster, but on the reverse strand, was demonstrated to specifically bind to the csa1 and cas1 promoters with the imperfect palindromic sequence. Importantly, it was demonstrated that the transcription level of csa1, cas1, cas2 and cas4 was significantly enhanced in a csa3a-overexpression strain and, moreover, the Csa1 and Cas1 protein levels were increased in this strain. Furthermore, we demonstrated the hyperactive uptake of unique spacers within both CRISPR loci in the presence of the csa3a overexpression vector. The spacer acquisition process is dependent on the CCN PAM sequence and protospacer selection is random and non-directional. These results suggested a regulation mechanism of CRISPR spacer acquisition where a single transcriptional regulator senses the presence of an invading element and then activates spacer acquisition gene expression which leads to de novo spacer uptake from the invading element

Zero-shot Medical Image Translation via Frequency-Guided Diffusion Models

Recently, the diffusion model has emerged as a superior generative model that can produce high quality and realistic images. However, for medical image translation, the existing diffusion models are deficient in accurately retaining structural information since the structure details of source domain images are lost during the forward diffusion process and cannot be fully recovered through learned reverse diffusion, while the integrity of anatomical structures is extremely important in medical images. For instance, errors in image translation may distort, shift, or even remove structures and tumors, leading to incorrect diagnosis and inadequate treatments. Training and conditioning diffusion models using paired source and target images with matching anatomy can help. However, such paired data are very difficult and costly to obtain, and may also reduce the robustness of the developed model to out-of-distribution testing data. We propose a frequency-guided diffusion model (FGDM) that employs frequency-domain filters to guide the diffusion model for structure-preserving image translation. Based on its design, FGDM allows zero-shot learning, as it can be trained solely on the data from the target domain, and used directly for source-to-target domain translation without any exposure to the source-domain data during training. We evaluated it on three cone-beam CT (CBCT)-to-CT translation tasks for different anatomical sites, and a cross-institutional MR imaging translation task. FGDM outperformed the state-of-the-art methods (GAN-based, VAE-based, and diffusion-based) in metrics of Frechet Inception Distance (FID), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity Index Measure (SSIM), showing its significant advantages in zero-shot medical image translation

High-quality genome assembly and comparative genomic profiling of yellowhorn (Xanthoceras sorbifolia) revealed environmental adaptation footprints and seed oil contents variations

Yellowhorn (Xanthoceras sorbifolia) is a species of deciduous tree that is native to Northern and Central China, including Loess Plateau. The yellowhorn tree is a hardy plant, tolerating a wide range of growing conditions, and is often grown for ornamental purposes in parks, gardens, and other landscaped areas. The seeds of yellowhorn are edible and contain rich oil and fatty acid contents, making it an ideal plant for oil production. However, the mechanism of its ability to adapt to extreme environments and the genetic basis of oil synthesis remains to be elucidated. In this study, we reported a high-quality and near gap-less yellowhorn genome assembly, containing the highest genome continuity with a contig N50 of 32.5 Mb. Comparative genomics analysis showed that 1,237 and 231 gene families under expansion and the yellowhorn-specific gene family NB-ARC were enriched in photosynthesis and root cap development, which may contribute to the environmental adaption and abiotic stress resistance of yellowhorn. A 3-ketoacyl-CoA thiolase (KAT) gene (Xso_LG02_00600) was identified under positive selection, which may be associated with variations of seed oil content among different yellowhorn cultivars. This study provided insights into environmental adaptation and seed oil content variations of yellowhorn to accelerate its genetic improvement

Control of Streptomyces alfalfae XY25T Over Clubroot Disease and Its Effect on Rhizosphere Microbial Community in Chinese Cabbage Field Trials

Clubroot caused by Plasmodiophora brassicae is one of the most destructive diseases in cruciferous crops. Streptomyces alfalfae XY25T, a biological control agent, exhibited great ability to relieve clubroot disease, regulate rhizosphere bacterial and fungal communities in Chinese cabbage, and promote its growth in greenhouse. Therefore, field experiments were carried out to investigate the effects of S. alfalfae XY25T on clubroot and rhizosphere microbial community in Chinese cabbage. Results showed that the control efficiency of clubroot by S. alfalfae XY25T was 69.4%. Applying the agent can alleviate soil acidification; increase the contents of soil organic matter, available nitrogen, available phosphorus, and available potassium; and enhance activities of invertase, urease, catalase, and alkaline phosphatase. During Chinese cabbage growth, bacterial diversity decreased first and then increased, and fungal diversity decreased gradually after inoculation with S. alfalfae XY25T. High-throughput sequencing analysis showed that the main bacterial phyla were Proteobacteria, Bacteroidetes, Acidobacteria, and Planctomycetes, and the major fungal phyla were Ascomycota and Basidiomycota in rhizosphere soil. The dominant bacterial genera were Flavobacterium, Candidatus, Pseudomonas, Stenotrophomonas, Sphingomonas, Flavisolibacter, and Gemmatimonbacteria with no significant difference in abundance, and the major fungal genera were Monographella, Aspergillus, Hypocreales, Chytridiaceae, Fusarium, Pleosporales, Agaricales, Mortierella, and Pleosporales. The significant differences were observed among Pleosporales, Basidiomycota, Colletotrichum, two strains attributed to Agaricales, and another two unidentified fungi by using S. alfalfae XY25T. Moreover, quantitative real-time PCR results indicated that P. brassicae content was significantly decreased after the agent inoculation. In conclusion, S. alfalfae XY25T can affect rhizosphere microbial communities; therefore, applying the agent is an effective approach to reduce the damage caused by clubroot