Deep Radio Observations and the Role of the Cosmic Web in Galaxy Evolution

A current open question in the evolution of galaxies, is what are the physical mechanisms that cut off galaxies from their primordial gas reservoirs, resulting in the end of their star-formation capabilities? Recent observational programs have shown that the properties of galaxies show dependencies on their placement within the large-scale structure (LSS) of the universe. These observations have motivated recent developments in theoretical work that have shown how a galaxy\u27s interaction with the LSS may impact its connection to primordial gas supply, and ability to continue to accrete gas, the fundamental ingredient in star-formation. In order to investigate the role of LSS in galaxy evolution, we use data from the COSMOS HI Large Extragalactic Survey (CHILES), a single pointing of the Very Large Array in the COSMOS field with the ability to detect HI in galaxies out to a redshift 0.45. We introduce a fast imaging pipeline that is able to produce science-ready image cubes of the CHILES data in a reasonable turnover time. This pipeline is applied to the full CHILES database and produces data of excellent sensitivity with minimal imaging artefacts. Additionally, we introduce the CHILES Continuum Polarization Survey (CHILES Con Pol), which is the most sensitive 1.4 GHz radio continuum survey, to date, at 4.5 resolution. We discuss the survey design, data processing, and comparison to other surveys taken in the COSMOS field and discuss their complementary aspects. Using these high quality sensitive radio data, and ancillary data from the COSMOS survey, we investigate neutral hydrogen content and relative star-formation rate for blue, lower mass spiral galaxies as a function of their placement in their LSS, for two redshift bins. We find that the neutral hydrogen content for galaxies not near the spine of filaments, more than 2 Mpc away, is lower in our low-z bin. We place this result in the context of recent theoretical work and speculate that we are observing recent cosmic web detachment events for galaxies of these types, that result in the cutting-off of galaxies from their primordial gas supply

Large Scale Structure in CHILES

We demonstrate that the Discrete Persistent Source Extractor (DisPerSE) can be used with spectroscopic redshifts to define the cosmic web and its distance to galaxies in small area deepfields. Here we analyze the use of DisPerSE to identify structure in observational data. We apply DisPerSE to the distribution of galaxies in the COSMOS field and find the best parameters to identify filaments. We compile a catalog of 11500 spectroscopic redshifts from the Galaxy and Mass Assembly (GAMA) G10 data release. We analyze two-dimensional slices, extract filaments and calculate the distance for each galaxy to its nearest filament. We find that redder and more massive galaxies are closer to filaments. To study the growth of galaxies across cosmic time, and environment, we are carrying out an HI survey covering redshifts z = 0 - 0.45, the COSMOS HI Large Extragalactic Survey (CHILES). In addition we present the predicted HI mass fraction as a function of distance to filaments for the spectroscopically known galaxies in CHILES. Lastly, we discuss the cold gas morphology of a few individual galaxies and their positions with respect to the cosmic web. The identification of the cosmic web, and the ability of CHILES to study the resolved neutral hydrogen morphologies and kinematics of galaxies, will allow future studies of the properties of neutral hydrogen in different cosmic web environments across the redshift range z = 0.1 - 0.45.Comment: Accepted for publication in the Astronomical Journal; 11 pages ; 8 figure

Kecernaan In-Sacco Bahan Kering, Bahan Organik, Dan Serat Kasar Daun Bangun-Bangun (Coleus amboinicus L) Yang Diproteksi Kapsul, Saponin Dan Tanin

Penelitian ini bertujuan untuk mengetahui kecernaan BK, BO dan SK pada daun bangun-bangun (Coleus amboinicus L) setelah dilakukan proteksi. Rancangan penelitian yang digunakan adalah rancangan acak lengkap (RAL) yang terdiri dari 4 perlakuan dan 5 ulangan. Perlakuan yang diberikan adalah memproteksi daun bangun-bangun P0 daun bangun-bagun tanpa perlakuan, P1 daun bangun-bangun di proteksi dengan kapsul, P2 daun bangun- bangun di proteksi daun kembang sepatu (saponin), P3 daun bangun-bangun di proteksi batang pisang (tanin). Peubah yang diamati yaitu kecernaan bahan kering (KcBK), kecernaan bahan organik (KcBO), dan kecernaan serat kasar (KcSK). Data diperoleh  dianalisis dengan analisis ragam. Jika berpengaruh nyata dilanjutkan dengan uji jarak Duncan. Hasil penelitian menunjukkan bahwa proteksi menggunakan kapsul, saponin dan tanin  berpengaruh nyata (P<0,05) terhadap KcBK, KcBO, dan KcSK daun bngun-bangun lebih lanjut terlihat pada P2 menunjukkan hasil yang baik dibandingkan P0, P1 dan P3. Hasil terbaik dicapai pada P2 yaitu proteksi menggunakan saponin yang di ekstrak dari daun kembang sepatu  dengan hasil kecernaan BK (83,56%), BO (83,61%), SK (83,02%) Berdasarkan hasil ini dapat disimpulkan bahan proteksi berupa saponin dapat memproteksi daun bangun-bangun dengan baik

Stam: a framework for spatio-temporal affordance maps

A�ordances have been introduced in literature as action op- portunities that objects o�er, and used in robotics to semantically rep- resent their interconnection. However, when considering an environment instead of an object, the problem becomes more complex due to the dynamism of its state. To tackle this issue, we introduce the concept of Spatio-Temporal A�ordances (STA) and Spatio-Temporal A�ordance Map (STAM). Using this formalism, we encode action semantics re- lated to the environment to improve task execution capabilities of an autonomous robot. We experimentally validate our approach to support the execution of robot tasks by showing that a�ordances encode accurate semantics of the environment

DEAD Box Protein DDX1 Regulates Cytoplasmic Localization of KSRP

mRNA decay mediated by the AU-rich elements (AREs) is one of the most studied post-transcriptional mechanisms and is modulated by ARE-binding proteins (ARE-BPs). To understand the regulation of K homology splicing regulatory protein (KSRP), a decay-promoting ARE-BP, we purified KSRP protein complexes and identified an RNA helicase, DDX1. We showed that down-regulation of DDX1 expression elevated cytoplasmic levels of KSRP and facilitated ARE-mediated mRNA decay. Association of KSRP with 14-3-3 proteins, that are predominately located in the cytoplasm, increased upon reduction of DDX1. We also demonstrated that KSRP associated with DDX1 or 14-3-3, but not both. These observations indicate that subcellular localization of KSRP is regulated by competing interactions with DDX1 or 14-3-3

Oxalate-Induced Damage to Renal Tubular Cells

Our own studies and those of others have shown that the incidence of calcium oxalate stones and plaques is markedly increased by nephrotoxins. The possible role of oxalate as a nephrotoxin has not been fully appreciated. However, recent studies in experimental animals and in cultured cells support this possibility. The results of these studies led us to hypothesize that hyperoxaluria promotes stone formation in several ways: by providing a substrate for the formation of the most common form of renal stones, calcium oxalate stones, and by inducing damage to renal epithelial cells. Damaged cells in turn would produce an environment favorable for crystal retention and provide membranous debris that promotes crystal nucleation, aggregation and adherence. The present report summarizes evidence for oxalate nephrotoxicity and discusses the potential importance of oxalate toxicity in the pathogenesis of stone disease

Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ

Protein quantification without isotopic labels has been a long-standing interest in the proteomics field. However, accurate and robust proteome-wide quantification with label-free approaches remains a challenge. We developed a new intensity determination and normalization procedure called MaxLFQ that is fully compatible with any peptide or protein separation prior to LC-MS analysis. Protein abundance profiles are assembled using the maximum possible information from MS signals, given that the presence of quantifiable peptides varies from sample to sample. For a benchmark dataset with two proteomes mixed at known ratios, we accurately detected the mixing ratio over the entire protein expression range, with greater precision for abundant proteins. The significance of individual label-free quantifications was obtained via a t test approach. For a second benchmark dataset, we accurately quantify fold changes over several orders of magnitude, a task that is challenging with label-based methods. MaxLFQ is a generic label-free quantification technology that is readily applicable to many biological questions; it is compatible with standard statistical analysis workflows, and it has been validated in many and diverse biological projects. Our algorithms can handle very large experiments of 500+ samples in a manageable computing time. It is implemented in the freely available MaxQuant computational proteomics platform and works completely seamlessly at the click of a button

Clinically Relevant Latent Space Embedding of Cancer Histopathology Slides through Variational Autoencoder Based Image Compression

In this paper, we introduce a Variational Autoencoder (VAE) based training approach that can compress and decompress cancer pathology slides at a compression ratio of 1:512, which is better than the previously reported state of the art (SOTA) in the literature, while still maintaining accuracy in clinical validation tasks. The compression approach was tested on more common computer vision datasets such as CIFAR10, and we explore which image characteristics enable this compression ratio on cancer imaging data but not generic images. We generate and visualize embeddings from the compressed latent space and demonstrate how they are useful for clinical interpretation of data, and how in the future such latent embeddings can be used to accelerate search of clinical imaging data

Predicting Future States with Spatial Point Processes in Single Molecule Resolution Spatial Transcriptomics

In this paper, we introduce a pipeline based on Random Forest Regression to predict the future distribution of cells that are expressed by the Sog-D gene (active cells) in both the Anterior to posterior (AP) and the Dorsal to Ventral (DV) axis of the Drosophila in embryogenesis process. This method provides insights about how cells and living organisms control gene expression in super resolution whole embryo spatial transcriptomics imaging at sub cellular, single molecule resolution. A Random Forest Regression model was used to predict the next stage active distribution based on the previous one. To achieve this goal, we leveraged temporally resolved, spatial point processes by including Ripley's K-function in conjunction with the cell's state in each stage of embryogenesis, and found average predictive accuracy of active cell distribution. This tool is analogous to RNA Velocity for spatially resolved developmental biology, from one data point we can predict future spatially resolved gene expression using features from the spatial point processes

CHILES: HI morphology and galaxy environment at z=0.12 and z=0.17

We present a study of 16 HI-detected galaxies found in 178 hours of observations from Epoch 1 of the COSMOS HI Large Extragalactic Survey (CHILES). We focus on two redshift ranges between 0.108 <= z <= 0.127 and 0.162 <= z <= 0.183 which are among the worst affected by radio frequency interference (RFI). While this represents only 10% of the total frequency coverage and 18% of the total expected time on source compared to what will be the full CHILES survey, we demonstrate that our data reduction pipeline recovers high quality data even in regions severely impacted by RFI. We report on our in-depth testing of an automated spectral line source finder to produce HI total intensity maps which we present side-by-side with significance maps to evaluate the reliability of the morphology recovered by the source finder. We recommend that this become a common place manner of presenting data from upcoming HI surveys of resolved objects. We use the COSMOS 20k group catalogue, and we extract filamentary structure using the topological DisPerSE algorithm to evaluate the \hi\ morphology in the context of both local and large-scale environments and we discuss the shortcomings of both methods. Many of the detections show disturbed HI morphologies suggesting they have undergone a recent interaction which is not evident from deep optical imaging alone. Overall, the sample showcases the broad range of ways in which galaxies interact with their environment. This is a first look at the population of galaxies and their local and large-scale environments observed in HI by CHILES at redshifts beyond the z=0.1 Universe.Comment: 23 pages, 12 figures, 1 interactive 3D figure, accepted to MNRA