What Makes Lyα\alpha Nebulae Glow? Mapping the Polarization of LABd05

"Ly$\alpha$ nebulae" are giant ($\sim$100 kpc), glowing gas clouds in the distant universe. The origin of their extended Ly$\alpha$ emission remains a mystery. Some models posit that Ly$\alpha$ emission is produced when the cloud is photoionized by UV emission from embedded or nearby sources, while others suggest that the Ly$\alpha$ photons originate from an embedded galaxy or AGN and are then resonantly scattered by the cloud. At least in the latter scenario, the observed Ly$\alpha$ emission will be polarized. To test these possibilities, we are conducting imaging polarimetric observations of seven Ly$\alpha$ nebulae. Here we present our results for LABd05, a cloud at $z$ = 2.656 with an obscured, embedded AGN to the northeast of the peak of Ly$\alpha$ emission. We detect significant polarization. The highest polarization fractions $P$ are $\sim$10-20% at $\sim$20-40 kpc southeast of the Ly$\alpha$ peak, away from the AGN. The lowest $P$, including upper-limits, are $\sim$5% and lie between the Ly$\alpha$ peak and AGN. In other words, the polarization map is lopsided, with $P$ increasing from the Ly$\alpha$ peak to the southeast. The measured polarization angles $\theta$ are oriented northeast, roughly perpendicular to the $P$ gradient. This unique polarization pattern suggests that 1) the spatially-offset AGN is photoionizing nearby gas and 2) escaping Ly$\alpha$ photons are scattered by the nebula at larger radii and into our sightline, producing tangentially-oriented, radially-increasing polarization away from the photoionized region. Finally we conclude that the interplay between the gas density and ionization profiles produces the observed central peak in the Ly$\alpha$ emission. This also implies that the structure of LABd05 is more complex than assumed by current theoretical spherical or cylindrical models.Comment: 11 pages, 8 figure

Mapping the Polarization of the Radio-Loud Lyα\alpha Nebula B3 J2330+3927

Lya nebulae, or "Lya blobs", are extended (up to ~100 kpc), bright (L[Lya] > 10^43 erg/s) clouds of Lya emitting gas that tend to lie in overdense regions at z ~ 2--5. The origin of the Lya emission remains unknown, but recent theoretical work suggests that measuring the polarization might discriminate among powering mechanisms. Here we present the first narrowband, imaging polarimetry of a radio-loud Lya nebula, B3 J2330+3927 at z=3.09, with an embedded active galactic nucleus (AGN). The AGN lies near the blob's Lya emission peak and its radio lobes align roughly with the blob's major axis. With the SPOL polarimeter on the 6.5m MMT telescope, we map the total (Lya + continuum) polarization in a grid of circular apertures of radius 0.6" (4.4kpc), detecting a significant (>2sigma) polarization fraction P in nine apertures and achieving strong upper-limits (as low as 2%) elsewhere. P increases from <2% at ~5kpc from the blob center to ~17% at ~15-25kpc. The detections are distributed asymmetrically, roughly along the nebula's major axis. The polarization angles theta are mostly perpendicular to this axis. Comparing the Lya flux to that of the continuum, and conservatively assuming that the continuum is highly polarized (20-100%) and aligned with the total polarization, we place lower limits on the polarization of the Lya emission P(Lya) ranging from no significant polarization at ~5 kpc from the blob center to ~ 3--17% at 10--25kpc. Like the total polarization, the Lya polarization detections occur more often along the blob's major axis.Comment: 9 pages, 7 figures, accepted for publication in Ap

Web-based design and analysis tools for CRISPR base editing

Background: As a result of its simplicity and high efficiency, the CRISPR-Cas system has been widely used as a genome editing tool. Recently, CRISPR base editors, which consist of deactivated Cas9 (dCas9) or Cas9 nickase (nCas9) linked with a cytidine or a guanine deaminase, have been developed. Base editing tools will be very useful for gene correction because they can produce highly specific DNA substitutions without the introduction of any donor DNA, but dedicated web-based tools to facilitate the use of such tools have not yet been developed. Results: We present two web tools for base editors, named BE-Designer and BE-Analyzer. BE-Designer provides all possible base editor target sequences in a given input DNA sequence with useful information including potential off-target sites. BE-Analyzer, a tool for assessing base editing outcomes from next generation sequencing (NGS) data, provides information about mutations in a table and interactive graphs. Furthermore, because the tool runs client-side, large amounts of targeted deep sequencing data (&lt; 1 GB) do not need to be uploaded to a server, substantially reducing running time and increasing data security. BE-Designer and BE-Analyzer can be freely accessed at http://www.rgenome.net/be-designer/ and http://www.rgenome.net/be-analyzer /, respectively. Conclusion: We develop two useful web tools to design target sequence (BE-Designer) and to analyze NGS data from experimental results (BE-Analyzer) for CRISPR base editors

Deep Learning for Integrated Analysis of Insulin Resistance with Multi-Omics Data

Technological advances in next-generation sequencing (NGS) have made it possible to uncover extensive and dynamic alterations in diverse molecular components and biological pathways across healthy and diseased conditions. Large amounts of multi-omics data originating from emerging NGS experiments require feature engineering, which is a crucial step in the process of predictive modeling. The underlying relationship among multi-omics features in terms of insulin resistance is not well understood. In this study, using the multi-omics data of type II diabetes from the Integrative Human Microbiome Project, from 10,783 features, we conducted a data analytic approach to elucidate the relationship between insulin resistance and multi-omics features, including microbiome data. To better explain the impact of microbiome features on insulin classification, we used a developed deep neural network interpretation algorithm for each microbiome feature’s contribution to the discriminative model output in the samples

Effects of Low pH and Low Salinity Induced by Meltwater Inflow on the Behavior and Physical Condition of the Antarctic Limpet, Nacella concinna

Seawater acidification and freshening in the intertidal zone of Marian Cove, Antarctica, which occurs by the freshwater inflow from snow fields and glaciers, could affect the physiology and behavior of intertidal marine organisms. In this study, we exposed Antarctic limpets, Nacella concinna, to two different pH (8.00 and 7.55) and salinity (34.0 and 27.0 psu) levels and measured their righting ability after being flipped over, mortality, condition factor, and shell dissolution. During the 35-day exposure, there was no significant difference in behavior and mortality between different treatments. However, the condition factor was negatively affected by low salinity. Both low pH and low salinity negatively influenced shell formation by decreasing the aragonite saturation state (&Omega;arg) and enhancing shell dissolution. Our results suggest that, though limpets can tolerate short-term low pH and salinity conditions, intrusions of meltwater accompanied by the glacial retreat may act as a serious threat to the population of N. concinna

Lightweight and Energy-Efficient Deep Learning Accelerator for Real-Time Object Detection on Edge Devices

Tiny machine learning (TinyML) has become an emerging field according to the rapid growth in the area of the internet of things (IoT). However, most deep learning algorithms are too complex, require a lot of memory to store data, and consume an enormous amount of energy for calculation/data movement; therefore, the algorithms are not suitable for IoT devices such as various sensors and imaging systems. Furthermore, typical hardware accelerators cannot be embedded in these resource-constrained edge devices, and they are difficult to drive real-time inference processing as well. To perform the real-time processing on these battery-operated devices, deep learning models should be compact and hardware-optimized, and hardware accelerator designs also have to be lightweight and consume extremely low energy. Therefore, we present an optimized network model through model simplification and compression for the hardware to be implemented, and propose a hardware architecture for a lightweight and energy-efficient deep learning accelerator. The experimental results demonstrate that our optimized model successfully performs object detection, and the proposed hardware design achieves 1.25× and 4.27× smaller logic and BRAM size, respectively, and its energy consumption is approximately 10.37× lower than previous similar works with 43.95 fps as a real-time process under an operating frequency of 100 MHz on a Xilinx ZC702 FPGA

Seawater carbonate chemistry and mortality and behavior of the Antarctic amphipod Gondogeneia antarctica

The Western Antarctic Peninsula (WAP) has experienced rapid atmospheric and ocean warming over the past few decades and many marine-terminating glaciers have considerably retreated. Glacial retreat is accompanied by fresh meltwater intrusion, which may result in the freshening and acidification of coastal waters. Marian Cove (MC), on King George Island in the WAP, undergoes one of the highest rates of glacial retreat. Intertidal and shallow subtidal waters are likely more susceptible to these processes, and sensitive biological responses are expected from the organisms inhabiting this area. The gammarid amphipod Gondogeneia antarctica is one of the most abundant species in the shallow, nearshore Antarctic waters, and it occupies an essential ecological niche in the coastal marine WAP ecosystem. In this study, we tested the sensitivity of G. antarctica to lowered salinity and pH by meltwater intrusion following glacial retreat. We exposed G. antarctica to four different treatments combining two salinities (34 and 27 psμ) and pH (8.0 and 7.6) levels for 26 days. Mortality, excluding cannibalized individuals, increased under low pH but decreased under low salinity conditions. Meanwhile, low salinity increased cannibalism, whereas low pH reduced food detection. Shelter use during the daytime decreased under each low salinity and pH condition, indicating that the two stressors act as disruptors of amphipod behavior. Under low salinity conditions, swimming increased during the daytime but decreased at night. Although interactions between low salinity and low pH were not observed during the experiment, the results suggest that each stressor, likely induced by glacial melting, causes altered behaviors in amphipods. These environmental factors may threaten population persistence in Marian Cove and possibly other similar glacial embayments

Suspension rheology of polyaniline coated manganese ferrite particles under electric/magnetic fields

Manganese ferrite (MnFe2O4) nanoparticles initially fabricated using a solvothermal process were coated with conducting polyaniline (PANI) to produce core/shell-structured MnFe2O4/PANI nanoparticles. An electro/magnetorheological (E/MR) fluid was prepared by suspending MnFe2O4/PANI particles in silicone oil, and the rheological properties under either electric or magnetic fields were investigated. Scanning electron microscope and transmission electron microscope provided the particle morphology and size information. X-ray diffraction and Fourier transform infrared spectroscopy were used to analyze the crystal structure and chemical composition of the particles. Chain formation in E/MR fluids under electric or magnetic fields was observed by optical microscopy, and the rheological properties were evaluated using a rheometer. Steady shear and dynamic oscillatory tests were conducted to confirm the effective E/MR characteristics while varying the electric/magnetic field strength. The dielectric properties of the particles measured using an LCR meter were analyzed based on the Cole-Cole model. The E/MR fluids composed of MnFe2O4/PANI showed a reversible and fast electro/magnetic response. © 2022FALS