Potential of Trap Crops for Integrated Management of the Tropical Armyworm, Spodoptera litura in Tobacco

The tropical armyworm, Spodoptera litura (F.) (Lepidoptera: Noctuidae), is an important pest of tobacco, Nicotiana tabacum L. (Solanales: Solanaceae), in South China that is becoming increasingly resistant to pesticides. Six potential trap crops were evaluated to control S. litura on tobacco. Castor bean, Ricinus communis L. (Malpighiales: Euphorbiaceae), and taro, Colocasia esculenta (L.) Schott (Alismatales: Araceae), hosted significantly more S. litura than peanut, Arachis hypogaea L. (Fabales: Fabaceae), sweet potato, Ipomoea batata Lam. (Solanales: Convolvulaceae) or tobacoo in a greenhouse trial, and tobacco field plots with taro rows hosted significantly fewer S. litura than those with rows of other trap crops or without trap crops, provided the taro was in a fast-growing stage. When these crops were grown along with eggplant, Solanum melongena L. (Solanales: Solanaceae), and soybean, Glycines max L. (Fabales: Fabaceae), in separate plots in a randomized matrix, tobacco plots hosted more S. litura than the other crop plots early in the season, but late in the season, taro plots hosted significantly more S. litura than tobacco, soybean, sweet potato, peanut or eggplant plots. In addition, higher rates of S. litura parasitism by Microplitis prodeniae Rao and Chandry (Hymenoptera: Bracondidae) and Campoletis chlorideae Uchida (Ichnumonidae) were observed in taro plots compared to other crop plots. Although taro was an effective trap crop for managing S. litura on tobacco, it did not attract S. litura in the seedling stage, indicating that taro should either be planted 20–30 days before tobacco, or alternative control methods should be employed during the seedling stage

Promotive role of IRF7 in ferroptosis of colonic epithelial cells in ulcerative colitis by the miR-375-3p/SLC11A2 axis

Ferroptosis is implicated in the progression of ulcerative colitis (UC), and interferon regulatory factor 7 (IRF7) contributes to cell death. This study probed the mechanism of IRF7 in ferroptosis of colonic epithelial cells (ECs) in mice with dextran sodium sulfate (DSS)-induced UC. The UC mouse model and the in vitro ferroptosis model were respectively established by DSS feeding and the treatment with FIN56 (a ferroptosis inducer). Results of quantitative real-time polymerase chain reaction and western blotting revealed the upregulation of IRF7 and solute carrier family 11 member 2 (SLC11A2/NRAMP2/DMT1) and the downregulation of microRNA (miR)-375-3p in DSS-treated mice and FIN56-treated ECs. Silencing of IRF7 improved the symptoms of UC in DSS-induced mice and decreased the levels of tumor necrosis factor α, interleukin 6, monocyte chemoattractant protein 1, and interleukin 1β, reactive oxygen species, iron ions, lipid peroxidation, and increased glutathione and glutathione peroxidase 4. Chromatin immunoprecipitation and dual-luciferase assays showed that binding of IRF7 to the miR-375-3p promoter inhibited miR-375-3p expression, and miR-375-3p suppressed SLC11A2 transcription. The rescue experiments revealed that knockdown of miR-375-3p neutralized the role of silencing IRF7 in alleviating ferroptosis of colonic ECs. Overall, IRF7 upregulated SLC11A2 transcription by inhibiting miR-375-3p expression, thereby prompting ferroptosis of colonic ECs and UC progression in DSS-treated mice

Three dimensional imaging of electrical trees in multiple stages

Electrical trees are degraded paths in polymeric insulation and are the mechanism of electrical failure of high voltage insulation systems. Previous studies have confirmed the application of X-ray Computed Tomography (XCT) imaging of electrical trees using phase contrast enhancement. This work evaluates the feasibility of X-ray imaging of electrical trees to measure growth at several stages of growth in the same treeing sample. The impact of x-ray dose on the epoxy resin studied is determined experimentally. An example of multi-stage tree imaging using laboratory micro-XCT and reconstructed renderings is provided. Based on the three-dimensional tree models, characteristics such as the degraded volume and surface area can be quantified. Furthermore, a comparison between two stages is presented to show the growth of the electrical tree in a fixed period of time. Insight into the treeing characteristics is also discussed

A novel prognostic 7-methylguanosine signature reflects immune microenvironment and alternative splicing in glioma based on multi-omics analysis

Glioma is the most common type of central nervous system tumor with increasing incidence. 7-methylguanosine (m7G) is one of the diverse RNA modifications that is known to regulate RNA metabolism and its dysregulation was associated with various cancers. However, the expression pattern of m7G regulators and their roles in regulating tumor immune microenvironments (TIMEs) as well as alternative splicing events (ASEs) in glioma has not been reported. In this study, we showed that m7G regulators displayed a close correlation with each other and most of them were differentially expressed between normal and glioma tissues. Two m7G signatures were then constructed to predict the overall survival of both GBM and LGG patients with moderate predictive performance. The risk score calculated from the regression coefficient and expression level of signature genes was proved to be an independent prognostic factor for patients with LGG, thus, a nomogram was established on the risk score and other independent clinical parameters to predict the survival probability of LGG patients. We also investigated the correlation of m7G signatures with TIMEs in terms of immune scores, expression levels of HLA and immune checkpoint genes, immune cell composition, and immune-related functions. While exploring the correlation between signature genes and the ASEs in glioma, we found that EIF4E1B was a key regulator and might play dual roles depending on glioma grade. By incorporating spatial transcriptomic data, we found a cluster of cells featured by high expression of PTN exhibited the highest m7G score and may communicate with adjacent cancer cells via SPP1 and PTN signaling pathways. In conclusion, our work brought novel insights into the roles of m7G modification in TIMEs and ASEs in glioma, suggesting that evaluation of m7G in glioma could predict prognosis. Moreover, our data suggested that blocking SPP1 and PTN pathways might be a strategy for combating glioma

Lessons from Three-Dimensional Imaging of Electrical Trees

Electrical trees are artifacts resulting from aging of polymeric insulation in high electrical fields. Whilst there is some debate concerning the mechanism by which they grow, there is no doubt that their growth can lead to the ultimate failure of the host insulation. Studying electrical trees is mainly confined to measurement of associated partial discharges and observing the physical growth of the tree structure optically. This paper reviews developments in observations of the growth of trees in the laboratory. In particular, consideration is given to the benefits of generating three-dimensional replicas of real trees from X-ray computer tomography (XCT) and serial block face scanning electron microscopy (SBFSEM), and how these can facilitate better understanding of tree development mechanisms. It is concluded that both two- and three-dimensional imaging are required, and these need correlating with partial discharge measurements to develop models of tree growth and effective asset management tools

Accelerating Quadratic Transform and WMMSE

Fractional programming (FP) arises in various communications and signal processing problems because several key quantities in the field are fractionally structured, e.g., the Cram\'{e}r-Rao bound, the Fisher information, and the signal-to-interference-plus-noise ratio (SINR). A recently proposed method called the quadratic transform has been applied to the FP problems extensively. The main contributions of the present paper are two-fold. First, we investigate how fast the quadratic transform converges. To the best of our knowledge, this is the first work that analyzes the convergence rate for the quadratic transform as well as its special case the weighted minimum mean square error (WMMSE) algorithm. Second, we accelerate the existing quadratic transform via a novel use of Nesterov's extrapolation scheme [1]. Specifically, by generalizing the minorization-maximization (MM) approach in [2], we establish a nontrivial connection between the quadratic transform and the gradient projection, thereby further incorporating the gradient extrapolation into the quadratic transform to make it converge more rapidly. Moreover, the paper showcases the practical use of the accelerated quadratic transform with two frontier wireless applications: integrated sensing and communications (ISAC) and massive multiple-input multiple-output (MIMO).Comment: 15 page

Event-Triggered Multi-Lane Fusion Control for 2-D Vehicle Platoon Systems with Distance Constraints

This paper investigates the event-triggered fixedtime multi-lane fusion control for vehicle platoon systems with distance keeping constraints where the vehicles are spread in multiple lanes. To realize the fusion of vehicles in different lanes, the vehicle platoon systems are firstly constructed with respect to a two-dimensional (2-D) plane. In case of the collision and loss of effective communication, the distance constraints for each vehicle are guaranteed by a barrier function-based control strategy. In contrast to the existing results regarding the command filter techniques, the proposed distance keeping controller can constrain the distance tracking error directly and the error generated by the command filter is coped with by adaptive fuzzy control technique. Moreover, to offset the impacts of the unknown system dynamics and the external disturbances, an unknown input reconstruction method with asymptotic convergence is developed by utilizing the interval observer technique. Finally, two relative threshold triggering mechanisms are utilized in the proposed fixed-time multi-lane fusion controller design so as to reduce the communication burden. The corresponding simulation results also verify the effectiveness of the proposed strategy

The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe

The preponderance of matter over antimatter in the early Universe, the dynamics of the supernova bursts that produced the heavy elements necessary for life and whether protons eventually decay --- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our Universe, its current state and its eventual fate. The Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed plan for a world-class experiment dedicated to addressing these questions. LBNE is conceived around three central components: (1) a new, high-intensity neutrino source generated from a megawatt-class proton accelerator at Fermi National Accelerator Laboratory, (2) a near neutrino detector just downstream of the source, and (3) a massive liquid argon time-projection chamber deployed as a far detector deep underground at the Sanford Underground Research Facility. This facility, located at the site of the former Homestake Mine in Lead, South Dakota, is approximately 1,300 km from the neutrino source at Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino charge-parity symmetry violation and mass ordering effects. This ambitious yet cost-effective design incorporates scalability and flexibility and can accommodate a variety of upgrades and contributions. With its exceptional combination of experimental configuration, technical capabilities, and potential for transformative discoveries, LBNE promises to be a vital facility for the field of particle physics worldwide, providing physicists from around the globe with opportunities to collaborate in a twenty to thirty year program of exciting science. In this document we provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess.Comment: Major update of previous version. This is the reference document for LBNE science program and current status. Chapters 1, 3, and 9 provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess. 288 pages, 116 figure

A Study of Unsupervised Evaluation Metrics for Practical and Automatic Domain Adaptation

Unsupervised domain adaptation (UDA) methods facilitate the transfer of models to target domains without labels. However, these methods necessitate a labeled target validation set for hyper-parameter tuning and model selection. In this paper, we aim to find an evaluation metric capable of assessing the quality of a transferred model without access to target validation labels. We begin with the metric based on mutual information of the model prediction. Through empirical analysis, we identify three prevalent issues with this metric: 1) It does not account for the source structure. 2) It can be easily attacked. 3) It fails to detect negative transfer caused by the over-alignment of source and target features. To address the first two issues, we incorporate source accuracy into the metric and employ a new MLP classifier that is held out during training, significantly improving the result. To tackle the final issue, we integrate this enhanced metric with data augmentation, resulting in a novel unsupervised UDA metric called the Augmentation Consistency Metric (ACM). Additionally, we empirically demonstrate the shortcomings of previous experiment settings and conduct large-scale experiments to validate the effectiveness of our proposed metric. Furthermore, we employ our metric to automatically search for the optimal hyper-parameter set, achieving superior performance compared to manually tuned sets across four common benchmarks. Codes will be available soon