Miracle-dz/UniFAR-FTUs huggingface dataset:
Breach History and Susceptibility Study, South Jetty and Navigation Project, Grays Harbor, Washington

The purpose of this study was to analyze the December 1993 breach at Grays Harbor, WA, and assess the threat to the Federal Navigation Project had the breach not been filled the following fall. The study was conducted by quantifying evolution of breach morphology; numerically simulating the ocean wave and water level conditions producing the current through such a breach, including investigation of wide-area implications for the current in Grays Harbor; and numerical modeling breach evolution. Available data on the breach evolution were analyzed with a Geographic Information System. The width of the breach and erosion of the adjacent shoreline are quantified from aerial photographs. Shoreline position and bottom configurations in the vicinity of the now-closed breach are the basis of numerical modeling of wave- and tide-driven currents. Estimates are made of the wave and current climate at South Beach, Pt. Chehalis, and in Half Moon Bay under the assumption of a breach at the jetty. Hydrodynamics for various alternatives of further erosion of the breach are modeled to evaluate flow patterns in a developed breach condition. Sediment transport and evolution of the breach are modeled to assess the potential for continued breach growth and long-term assessment of breach stability. Study products are intended to assist the U.S. Army Engineer District, Seattle, in developing a long-term management plan for protecting Federal navigation project features.
Structural evidence for Scc4-dependent localization of cohesin loading

The cohesin ring holds newly replicated sister chromatids together until their separation at anaphase. Initiation of sister chromatid cohesion depends on a separate complex, Scc2NIPBL/Scc4Mau2 (Scc2/4), which loads cohesin onto DNA and determines its localization across the genome. Proper cohesin loading is essential for cell division, and partial defects cause chromosome missegregation and aberrant transcriptional regulation, leading to severe developmental defects in multicellular organisms. We present here a crystal structure showing the interaction between Scc2 and Scc4. Scc4 is a TPR array that envelops an extended Scc2 peptide. Using budding yeast, we demonstrate that a conserved patch on the surface of Scc4 is required to recruit Scc2/4 to centromeres and to build pericentromeric cohesion. These findings reveal the role of Scc4 in determining the localization of cohesin loading and establish a molecular basis for Scc2/4 recruitment to centromeres. DOI: http://dx.doi. org/10.7554/eLife.06057. 001
Edinburgh Research Explorer Structural and Biophysical Studies on Two Promoter Recognition Domains of the Extra-cytoplasmic Function Factor C from Mycobacterium tuberculosis

Summary σ factors are transcriptional regulatory proteins that bind to the RNA polymerase and dictate gene expression. The extracytoplasmic function σ factors (ECF) govern the environment dependent regulation of transcription. ECF σ factors have two domains σ 2 and σ 4 that recognize the − 10 and − 35 promoter elements. However, unlike the primary σ factor σ A , the ECF σ factors lack σ 3 , a region that helps in the recognition of the extended − 10 element and σ 1.1 , a domain involved in the auto-inhibition of σ A in the absence of core RNA polymerase. Mycobacterium tuberculosis σ C is an ECF σ factor that is essential for the pathogenesis and virulence of M. tuberculosis in the mouse and guinea pig models of infection. However, unlike other ECF σ factors, σ C does not appear to have a regulatory anti- σ factor located in the same operon. We also note that Mycobacterium tuberculosis σ C differs from the canonical ECF σ factors as it has an N-terminal domain comprising of 126 amino acids that precedes the σ C2 and σ C4 domains. In an effort to understand the regulatory mechanism of this protein, the crystal structures of the σ C2 and σ C4 domains of σ C were determined. These promoter recognition domains are structurally similar to the corresponding domains of σ A despite the low sequence similarity. Fluorescence experiments using the intrinsic tryptophan residues of σ C2 as well as surface plasmon resonance measurements reveal that the σ C2 and σ C4 domains interact with each other. Mutational analysis suggests that the Pribnow box binding region of σ C2 is involved in this interdomain interaction. Interaction between the promoter recognition domains in M. tuberculosis σ C are thus likely to regulate the activity of this protein even in the absence of an anti- σ factor.
Research in Computational Molecular Biology

Transcriptional interactions in a cell are modulated by a variety of mechanisms that prevent their representation as pure pairwise interactions between a transcription factor and its target(s). These include, among others, transcription factor activation by phosphorylation and acetylation, formation of active complexes with one or more co-factors, and mRNA/protein degradation and stabilization processes. This paper presents a first step towards the systematic, genome-wide computational inference of genes that modulate the interactions of specific transcription factors at the post-transcriptional level. The method uses a statistical test based on changes in the mutual information between a transcription factor and each of its candidate targets, conditional on the expression of a third gene. The approach was first validated on a synthetic network model, and then tested in the context of a mammalian cellular system. By analyzing 254 microarray expression profiles of normal and tumor related human B lymphocytes, we investigated the post transcriptional modulators of the MYC proto-oncogene, an important transcription factor involved in tumorigenesis. Our method discovered a set of 100 putative modulator genes, responsible for modulating 205 regulatory relationships between MYC and its targets. The set is significantly enriched in molecules with function consistent with their activities as modulators of cellular interactions, recapitulates established MYC regulation pathways, and provides a notable repertoire of novel regulators of MYC function. The approach has broad applicability and can be used to discover modulators of any other transcription factor, provided that adequate expression profile data are available.
The El Niño-Southern Oscillation Phenomenon

Preface 1. Preview 2. The observational basis 3. The equations of motion and some simplifications 4. Boundary layers on both sides of the tropical ocean surface 5. Atmospheric processes 6. Ocean processes 7. ENSO mechanisms 8. ENSO prediction and short term climate prediction 9. ENSO, past and future, or ENSO by proxy and ENSO in the tea leaves 10. Using ENSO information 11. Postview Appendix 1. Some useful numbers Appendix 2. The parabolic cylinder functions Appendix 3. Modal and non-modal growth References Index.
Exploring and supporting second language identity development among adult ESL learners

Summary: The three primary goals of this article are to explore the research in adult ESL learner populations relating to L2 identities; to center the adult ESL learners’ L2 identity development through conferencing and reflection journals; and to recommend practical tools to facilitate the conversation among advanced adult ESL learners in their L2 identity development.
Therapeutic Angiogenesis: Foundations and Practical Application

Angiogenesis as therapeutic target has emerged since early works by Judah Folkman, yet his “holy grail” was inhibiting vascular growth to block tumor nutrition. However, in modern biomedicine, “therapeutic angiogenesis” became a large field focusing on stimulation of blood vessel growth for ischemia relief to reduce its detrimental effects in the tissues. In this review, we introduce basic principles of tissue vascularization in response to ischemia exploited in this field. An overview of recent status in therapeutic angiogenesis is given with introduction to emerging technologies, including gene therapy, genetic modification of cells ex vivo and tissue engineering.
Data-driven surrogate modeling of high-resolution sea-ice thickness in the Arctic

A novel generation of sea-ice models with Elasto-Brittle rheologies, such as neXtSIM, can represent sea-ice processes with an unprecedented accuracy at the mesoscale, for resolutions of around 10km . As these models are computationally expensive, we introduce supervised deep learning techniques for surrogate modeling of the sea-ice thickness from neXtSIM simulations. We adapt a convolutional UNet architecture to an Arctic-wide setup by taking the land-sea mask with partial convolutions into account. Trained to emulate the sea-ice thickness on a lead time of 12 hours, the neural network can be iter-5 atively applied to predictions up to a year. The improvements of the surrogate model over a persistence forecast prevail from 12 hours to roughly a year, with improvements of up to 50% in the forecast error. The predictability of the sea-ice thickness measured against a daily climatology additionally lays by around 8 months. By using atmospheric forcings as additional input, the surrogate model can represent advective and thermodynamical processes, which influence the sea-ice thickness and the growth and melting therein. While iterating, the surrogate model experiences diffusive processes, which result into a loss of 10 fine-scale structures. However, this smoothing increases the coherence of large-scale features and hereby the stability of the model. Therefore, based on these results, we see a huge potential for surrogate modelling of state-of-art sea-ice models with neural networks.
Issues Involving Vocabulary Learning and Teaching: A Study of the Literature

In this paper, I will attempt to bring out the discussion and studies that have been carried out in the domain of second language vocabulary learning and teaching. To this end, I have examined the existing literature to highlight the conditions required for vocabulary learning and types of vocabulary learning. I have also presented a discussion on the different types of vocabulary teaching and the factors affecting it. The paper begins with a general introduction to vocabulary as a language component and its role in building second language proficiency. It ends with a discussion on the need to recognize the various vocabulary learning types and conditions by the teacher, so that they can make changes in their teaching techniques to maximize the scope for vocabulary learning.
TOWARDS THE IMPLEMENTATION OF TRAVEL DEMAND MANAGEMENT IN SOUTH AFRICAN CITIES

Over the past years, transportation demand management (TDM) has moved from an idea warranting greater investigation and understanding in the South African urban environment to a promising management technique deserving initial implementation action in the form of pilot projects and general public debate. As a response to government policy, TDM is needed to support improved spatial planning and efficient public transit, and would also offer significant environmental benefits. A pilot project is currently underway in Midrand and if successful the concept may be applied in other urban areas.
Sensitivity of BEACON to Point Sources of Ultrahigh Energy Neutrinos

The Beamforming Elevated Array for COsmic Neutrinos (BEACON) is a novel detector concept designed to measure the tau neutrino flux above 100 PeV. BEACON consists of multiple radio interferometers placed on mountaintops which search for the radio emission of upgoing extensive air showers created when tau neutrinos skim the Earth. Each interferometer consists of O( 10 ) low cost, dual-polarized dipole antennas operating in a phased array, which allows for lower trigger thresholds and the directional rejection of noise. A full-scale BEACON will consist of O( 1000 ) independent antenna arrays and is predicted to be sensitive to the diffuse flux of cosmogenic neutrinos. A Monte Carlo simulation utilizing models of air shower radio emission and the BEACON antennas was developed to predict the sensitivity of BEACON to point sources of tau neutrinos. Any number and configuration of BEACON stations can be simulated. Here, we present the predicted point source sensitivity of a 1,000 station BEACON and compare it to the expected fluence from different possible neutrino sources
Backward wave oscillation suppression study of the helix travelling wave tube

ABSTRACT In this paper, the effect of backward wave oscillation (BWO) on helix slow wave structure performance for TWT has been described. In this paper both the cases tapered and untapered helix slow wave structure (SWS) have been analyzed, caused by BWO for high gain helix TWT. In house developed the one-dimensional (SUNRAY-1D) large signal analysis model has been used for stability analysis of the helix SWS. The analysis on backward wave amplifier gain has been carried out as a function of the taper parameter and frequency parameter. The position and nature of tapering also affect the electronic efficiency as well as the start oscillation current. Hence, position and nature of tapering have been optimized.
Universal Ring-of-Abusers Detection via Multi-Modal Heterogeneous Graph Learning

As fraudulent and abusive activities performed by groups continue to plague e-commerce stores, we realize that detecting groups of abusers, or Ring-of-Abusers (RoAs), has become crucial. Unlike existing works about abuser detection on e-commerce stores that merely consider the individual features of abusers or the relationships among abusers, we design a U niversal R ing-O f-A busers D etection framework (abbreviated as U-ROAD ) that integrates multi-modal features (e.g., numerical feature, text, and image) and the rich relationships among entities (i.e., seller, buyer, and product) on e-commerce stores. Especially, the U-ROAD framework designs three meta-paths to depict the high-order heterogeneous semantic relationships among entities. Then it leverages graph neural networks (GNNs) for obtaining the semantic node embeddings, which are fused with an aggregation layer and fed to an MLP classifier to detect abusers (e.g., abusive sellers and buyers) in different scenarios. As a result, (i): Flexible : The U-ROAD framework can be easily customized with different training labels to detect different types of abusers at e-commerce stores (e.g., rank abusers, financial abusers, and competitor abusers). (ii): Powerful and Timely : The framework is empirically powerful than some existing methods, which achieves an average 30% improvement in precision and 7.5% improvement in recall on four abuser (i.e., abusive seller and abusive buyer) detection tasks in two stores. Besides, our U-ROAD framework can detect abusers earlier than some existing methods on e-commerce stores. (iii): Explainable : The U-ROAD framework develops a visualization tool to help investigators understand the RoAs detection results.
Clinical Condition: Radiographically Detected Solitary Pulmonary Nodule

The ACR Committee on Appropriateness Criteria and its expert panels have developed criteria for determining appropriate imaging examinations for diagnosis and treatment of specified medical condition(s). These criteria are intended to guide radiologists, radiation oncologists and referring physicians in making decisions regarding radiologic imaging and treatment. Generally, the complexity and severity of a patient’s clinical condition should dictate the selection of appropriate imaging procedures or treatments. Only those examinations generally used for evaluation of the patient’s condition are ranked. Other imaging studies necessary to evaluate other co-existent diseases or other medical consequences of this condition are not considered in this document. The availability of equipment or personnel may influence the selection of appropriate imaging procedures or treatments. Imaging techniques classified as investigational by the FDA have not been considered in developing these criteria; however, study of new equipment and applications should be encouraged. The ultimate decision regarding the appropriateness of any specific radiologic examination or treatment must be made by the referring physician and radiologist in light of all the circumstances presented in an individual examination.
Cognitive Affordance Representations in Uncertain Logic

Natural human activities involve applying cognitive skills to use and manipulate objects around us, often several at a time, simultaneously and continuously. Consider the simple act of doodling, which requires several cognitive skills: (1) choosing how to grasp a pencil, (2) sequencing actions like drawing and erasing, and (3) reasoning about various social norms like if the paper were not scrap, then it might be inappropriate to scribble on it. Additionally, the doodler must make creative decisions about the content and form of the drawing itself. Learning how to use objects is a highly desirable skill for artificial agents, as well. Helper agents are becoming a part of the vision of our future: helping our elderly and disabled in assisted living facilities, conducting search-andrescue missions in unforgiving terrain to save human lives, assisting our astronauts on the space station, or even monitoring our surroundings to keep us safe from national security threats. Unfortunately, although artificial agents are proficient at recognizing object features, they are less-skilled at recognizing what can be done with these objects (i.e., they cannot perceive complex object affordances). My research seeks to build an integrated computational framework for representing and reasoning about not only an object’s physical features, but also higher-order functional, social, aesthetic, ethical and moral aspects (i.e., cognitive affordances). Towards this goal, I am developing a novel approach based on first-order “uncertain logic” and DempsterShafer (DS) probabilistic theory for inferring cognitive affordances.
Robust profile decomposition for large extragalactic spectral-line surveys

We present a novel algorithm that is based on a Bayesian Markov Chain Monte Carlo (MCMC) technique for performing robust profile analysis of a data cube from either single-dish or interferometric radio telescopes. It fits a set of models comprised of a number of Gaussian components given by the user to individual line-of-sight velocity profiles, then compares them and finds an optimal model based on the Bayesian Inference Criteria computed for each model.The decomposed Gaussian components are then classified into bulk or non-circular motions as well as kinematically cold or warm components. The fitting based on the Bayesian MCMC technique is insensitive to initial estimates of the parameters, and suffers less from finding the global minimum in models given enough sampling points and a wide range of priors for the parameters. It is found to provide reliable profile decomposition and classification of the decomposed components in a fully automated way, together with robust error estimation of the parameters as shown by performance tests using artificial data cubes. We apply the newly developed algorithm to the HI data cubes of sample galaxies from the Local Volume HI galaxy Survey (LVHIS). We also compare the kinematically cold and warm components, and bulk velocity fields with previous analyses made in a classical method.
Disentangling the drivers of future Antarctic ice loss with a historically calibrated ice-sheet model

Abstract. We use an observationally calibrated ice-sheet model to investigate the future trajectory of the Antarctic ice sheet related to uncertainties in the future balance between sub-shelf melting and ice discharge, on the one hand, and the surface mass balance, on the other. Our ensemble of simulations, forced by a panel of climate models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6), suggests that the ocean will be the primary driver of short-term Antarctic mass loss, initiating ice loss in West Antarctica already during this century. The atmosphere initially plays a mitigating role through increased snowfall, leading to an Antarctic contribution to global mean sea-level rise by 2100 of 6 (−8 to 15) cm under a low-emission scenario and 5.5 (−10 to 16) cm under a very high-emission scenario. However, under the very high-emission pathway, the influence of the atmosphere shifts beyond the end of the century, becoming an amplifying driver of mass loss as the ice sheet's surface mass balance decreases. We show that this transition occurs when Antarctic near-surface warming exceeds a critical threshold of +7.5 ∘C, at which the increase in surface runoff outweighs the increase in snow accumulation, a signal that is amplified by the melt–elevation feedback. Therefore, under the very high-emission scenario, oceanic and atmospheric drivers are projected to result in a complete collapse of the West Antarctic ice sheet along with significant grounding-line retreat in the marine basins of the East Antarctic ice sheet, leading to a median global mean sea-level rise of 2.75 (6.95) m by 2300 (3000). Under a more sustainable socio-economic pathway, we find that the Antarctic ice sheet may still contribute to a median global mean sea-level rise of 0.62 (1.85) m by 2300 (3000). However, the rate of sea-level rise is significantly reduced as mass loss is likely to remain confined to the Amundsen Sea Embayment, where present-day climate conditions seem sufficient to commit to a continuous retreat of Thwaites Glacier.
Steering Fallible Consumers

Online intermediaries with information about a consumer’s tendencies often “steer” her toward products she is more likely to purchase. We analyse the welfare implications of this practice for “fallible” consumers, who make statistical and strategic mistakes in evaluating offers. The welfare effects depend on the nature and quality of the intermediary’s information and on properties of the consumer’s mistakes. In particular, steering based on high-quality information about the consumer’s mistakes is typically harmful, sometimes extremely so. We argue that much real-life steering is of this type, raising the scope for a broader regulation of steering practices.
Clinical, Echocardiographic, and Longitudinal Characteristics Associated with Heart Failure with Improved Ejection Fraction

Background: Heart failure (HF) with improved ejection fraction (HFimpEF) has better outcomes than HF with reduced ejection fraction (HFrEF). However, factors contributing to HFimpEF remain unclear. This study aimed to evaluate clinical and longitudinal characteristics associated with subsequent HFimpEF. Methods: This was a single-center retrospective HFrEF cohort study. Data were collected from 2014 to 2022. Patients with HFrEF were identified using ICD codes, echocardiographic data, and natriuretic peptide levels. The main endpoints were HFimpEF (defined as ejection fraction >40% at [≥]3 months with [≥]10% increase) and mortality. Cox proportional hazards and mixed effects models were used for analyses. Results: The study included 1307 HFrEF patients with a median follow-up of 16.3 months (IQR 8.0-30.6). The median age was 65 years; 68% were male while 57% were white. On follow-up, 39% (n=506) developed HFimpEF, while 61% (n=801) had persistent HFrEF. A multivariate Cox regression model identified sex, race comorbidities, echocardiographic, and natriuretic peptide as significant covariates of HFimpEF (p<0.05). The HFimpEF group had better survival compared to the persistent HFrEF group (p<0.001). Echocardiographic and laboratory trajectories differed between groups. Conclusion: In this HFrEF cohort, 39% transitioned to HFimpEF and approximately 50% met the definition within the first 12 months. In a HFimpEF model, sex, comorbidities, echocardiographic parameters, and natriuretic peptide were associated with subsequent HFimpEF. The model has the potential to identify patients at risk of subsequent persistent or improved HFrEF, thus informing the design and implementation of targeted quality-of-care improvement interventions.