Supernova Axion Emissivity with Δ(1232)\Delta(1232) Resonance in Heavy Baryon Chiral Perturbation Theory

In this paper, we evaluate the energy loss rate of supernovae induced by the axion emission process $\pi^- + p \to n + a$ with the $\Delta(1232)$ resonance in the heavy baryon chiral perturbation theory for the first time. Given the axion-nucleon-$\Delta$ interactions, we include the previously ignored $\Delta$-mediated graphs to the $\pi^- + p \to n + a$ process. In particular, the $\Delta^0$-mediated diagram can give a resonance contribution to the supernova axion emission rate when the center-of-mass energy of the pion and proton approaches the $\Delta(1232)$ mass. With these new contributions, we find that for the typical supernova temperatures, compared with the earlier work with the axion-nucleon (and axion-pion-nucleon contact) interactions, the supernova axion emissivity can be enhanced by a factor of $\sim$4(2) in the Kim-Shifman-Vainshtein-Zakharov model and up to a factor of $\sim$5(2) in the Dine-Fischler-Srednicki-Zhitnitsky model with small $\tan\beta$ values. Remarkably, we notice that the $\Delta(1232)$ resonance gives a destructive contribution to the supernova axion emission rate at high supernova temperatures, which is a nontrivial result in this study.Comment: 17 pages, 4 figures, typo is fixed, references updated. Matches version published in Physical Review

SupSiam: Non-contrastive Auxiliary Loss for Learning from Molecular Conformers

We investigate Siamese networks for learning related embeddings for augmented samples of molecular conformers. We find that a non-contrastive (positive-pair only) auxiliary task aids in supervised training of Euclidean neural networks (E3NNs) and increases manifold smoothness (MS) around point-cloud geometries. We demonstrate this property for multiple drug-activity prediction tasks while maintaining relevant performance metrics, and propose an extension of MS to probabilistic and regression settings. We provide an analysis of representation collapse, finding substantial effects of task-weighting, latent dimension, and regularization. We expect the presented protocol to aid in the development of reliable E3NNs from molecular conformers, even for small-data drug discovery programs.Comment: Submitted to the MLDD workshop, ICLR 202

M3FPolypSegNet: Segmentation Network with Multi-frequency Feature Fusion for Polyp Localization in Colonoscopy Images

Polyp segmentation is crucial for preventing colorectal cancer a common type of cancer. Deep learning has been used to segment polyps automatically, which reduces the risk of misdiagnosis. Localizing small polyps in colonoscopy images is challenging because of its complex characteristics, such as color, occlusion, and various shapes of polyps. To address this challenge, a novel frequency-based fully convolutional neural network, Multi-Frequency Feature Fusion Polyp Segmentation Network (M3FPolypSegNet) was proposed to decompose the input image into low/high/full-frequency components to use the characteristics of each component. We used three independent multi-frequency encoders to map multiple input images into a high-dimensional feature space. In the Frequency-ASPP Scalable Attention Module (F-ASPP SAM), ASPP was applied between each frequency component to preserve scale information. Subsequently, scalable attention was applied to emphasize polyp regions in a high-dimensional feature space. Finally, we designed three multi-task learning (i.e., region, edge, and distance) in four decoder blocks to learn the structural characteristics of the region. The proposed model outperformed various segmentation models with performance gains of 6.92% and 7.52% on average for all metrics on CVC-ClinicDB and BKAI-IGH-NeoPolyp, respectively.Comment: 5pages. 2023 IEEE International Conference on Image Processing (ICIP). IEEE, 202

Evaluation of the efficacy of ivermectin against Theileria orientalis infection in grazing cattle

Background Raising cattle on pastures is known to be beneficial for animal welfare and cost reduction. However, grazing is associated with the risk of contracting tick-borne diseases, such as theileriosis. Here, the efficacy of ivermectin against these diseases and associated clinical symptoms were evaluated. Results A total of 68 cattle from a grazing cattle farm were selected and divided into two groups: the control group (17 cattle) with no preventive treatment and the ivermectin-treated group (51 cattle) in which cattle were treated with pour-on ivermectin prior to grazing. The infection rates of Theileria orientalis and the red blood cell (RBC) profile (e.g., RBC count, hematocrit value, and hemoglobin concentration) were compared in the spring (before grazing) and summer (during grazing) between the two groups. Based on PCR amplification of the major piroplasm surface protein (MPSP) gene, 12 cattle were positive for T. orientalis infection. Phylogenetic analysis revealed that the isolates identified in this study consisted of three MPSP types (1, 2, and 7). The T. orientalis infection rate in the control group during grazing was 3-fold higher than that in the ivermectin-treated group. Moreover, differences in RBC parameters during grazing were greater in the control group than in the ivermectin-treated group. In particular, the hematocrit value was significantly reduced in the control group. Conclusions The results of this study demonstrated that ivermectin had protective effects against T. orientalis infection and RBC hemolysis in grazing cattle.This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF2017R1A2B2005685). This research was partially supported by Technology Development Program (Project No. 1116043–1) for Bio-industry, Ministry for Agriculture, Food and Rural Affairs, Republic of Korea. The funders had no role in the study design, data collection and analysis, interpretation of results, writing of the report, decision to submit the paper for publication

Meteorological characteristics and assessment of the effect of local emissions during high PM10 concentration in the Seoul Metropolitan Area

In this study, we investigate the meteorological characteristics and the effect of local emissions during high PM10 concentrations in the Seoul Metropolitan Area (SMA) by utilizing data from a high-resolution urban meteorological observation system network (UMS-Seoul) and The Air Pollution Model (TAPM). For a detailed analysis, days with PM10 concentrations higher than 80 ??g m-3 for daily average PM10 concentration (classified as unhealthy by the Korean Ministry of Environment) in the Seoul Metropolitan Area (SMA) were classified into 3 Cases. Case I was defined as when the prevailing effect was from outside the SMA. Case II was defined as when the prevailing effect was a local effect with outside. Case III was defined as when the prevailing effect was local. Overall, high PM10 concentrations in the SMA mostly occurred under weak migratory anticyclone systems over the Korean Peninsula during warm temperatures. Prior to the PM10 concentration reaching the peak concentration, the pattern in each case was distinctive. After peak concentrations, however, the pattern for the 3 cases became less distinct. This study showed that nearly 50% of the high PM10 concentrations in the SMA occurred in spring and were governed by the conditions for Case II more than these for Cases I and III. In spring, the main sources of the high PM10 concentrations in the SMA were local emissions due to the predominance of weak winds and local circulation. The simulation showed that the non-SMA emissions were about 63 to 73% contribution to the spring high PM10 concentrations in the SMA. Specifically, local point sources including industrial combustion, electric utility, incineration and cement production facilities scattered around the SMA and could account for PM10 concentrations more than 10 ??g m-3 in the SMA

Far-infrared imaging antenna arrays

A far-infrared imaging antenna array has been demonstrated for the first time. The array is a line of evaporated silver bow-tie antennas on a fused-quartz substrate with bismuth-microbolometer detectors. The measured optical transfer function shows that the system is diffraction limited. This imaging array should find direct application in fusion plasma diagnostics. If the microbolometers can be replaced by more sensitive diode detectors, the array should also find application in radiometry and radar

Clinical MetaData ontology: a simple classification scheme for data elements of clinical data based on semantics

Background The increasing use of common data elements (CDEs) in numerous research projects and clinical applications has made it imperative to create an effective classification scheme for the efficient management of these data elements. We applied high-level integrative modeling of entire clinical documents from real-world practice to create the Clinical MetaData Ontology (CMDO) for the appropriate classification and integration of CDEs that are in practical use in current clinical documents. Methods CMDO was developed using the General Formal Ontology method with a manual iterative process comprising five steps: (1) defining the scope of CMDO by conceptualizing its first-level terms based on an analysis of clinical-practice procedures, (2) identifying CMDO concepts for representing clinical data of general CDEs by examining how and what clinical data are generated with flows of clinical care practices, (3) assigning hierarchical relationships for CMDO concepts, (4) developing CMDO properties (e.g., synonyms, preferred terms, and definitions) for each CMDO concept, and (5) evaluating the utility of CMDO. Results We created CMDO comprising 189 concepts under the 4 first-level classes of Description, Event, Finding, and Procedure. CMDO has 256 definitions that cover the 189 CMDO concepts, with 459 synonyms for 139 (74.0%) of the concepts. All of the CDEs extracted from 6 HL7 templates, 25 clinical documents of 5 teaching hospitals, and 1 personal health record specification were successfully annotated by 41 (21.9%), 89 (47.6%), and 13 (7.0%) of the CMDO concepts, respectively. We created a CMDO Browser to facilitate navigation of the CMDO concept hierarchy and a CMDO-enabled CDE Browser for displaying the relationships between CMDO concepts and the CDEs extracted from the clinical documents that are used in current practice. Conclusions CMDO is an ontology and classification scheme for CDEs used in clinical documents. Given the increasing use of CDEs in many studies and real-world clinical documentation, CMDO will be a useful tool for integrating numerous CDEs from different research projects and clinical documents. The CMDO Browser and CMDO-enabled CDE Browser make it easy to search, share, and reuse CDEs, and also effectively integrate and manage CDEs from different studies and clinical documents.This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number:HI18C2386). KHIDI had no participation in the study design or data collection and analysis process. KHIDI did not participate in the writing of the manuscript