Miracle-dz/UniFAR-FTUs huggingface dataset:
Engineering a ribozyme cleavage-induced split fluorescent aptamer complementation assay

Abstract Hammerhead ribozymes are self-cleaving RNA molecules capable of regulating gene expression in living cells. Their cleavage performance is strongly influenced by intra-molecular loop–loop interactions, a feature not readily accessible through modern prediction algorithms. Ribozyme engineering and efficient implementation of ribozyme-based genetic switches requires detailed knowledge of individual self-cleavage performances. By rational design, we devised fluorescent aptamer-ribozyme RNA architectures that allow for the real-time measurement of ribozyme self-cleavage activity in vitro. The engineered nucleic acid molecules implement a split Spinach aptamer sequence that is made accessible for strand displacement upon ribozyme self-cleavage, thereby complementing the fluorescent Spinach aptamer. This fully RNA-based ribozyme performance assay correlates ribozyme cleavage activity with Spinach fluorescence to provide a rapid and straightforward technology for the validation of loop–loop interactions in hammerhead ribozymes.
Antipode: Enforcing Cross-Service Causal Consistency in Distributed Applications

Modern internet-scale applications suffer from cross-service inconsistencies, arising because applications combine multiple independent and mutually-oblivious datastores. The end-to-end execution flow of each user request spans many different services and datastores along the way, implicitly establishing ordering dependencies among operations at different datastores. Readers should observe this ordering and, in today's systems, they do not. In this work, we present Antipode, a bolt-on technique for preventing cross-service consistency violations in distributed applications. It enforces cross-service consistency by propagating lineages of datastore operations both alongside end-to-end requests and within datastores. Antipode enables a novel cross-service causal consistency model, which extends existing causality models, and whose enforcement requires us to bring in a series of technical contributions to address fundamental semantic, scalability, and deployment challenges. We implemented Antipode as an application-level library, which can easily be integrated into existing applications with minimal effort, is incrementally deployable, and does not require global knowledge of all datastore operations. We apply Antipode to eight open-source and public cloud datastores and two microservice benchmark applications. Our evaluation demonstrates that Antipode is able to prevent cross-service inconsistencies with limited programming effort and less than 2% impact on end-user latency and throughput.
The Use of Spot Image for Mangrove Inventory in Cimanuk Delta West Java, Indonesia

This study deals with an application of SPOT satellite data for mangrove forest inventory in Cimauuk Delta West Java (Indonesia). Mangrove of the area (7100 Ha) has been gradually decreasing by human pressure especially for fisheries purposes. In fact, mangrove here is a result of afforestation since1960, with Rhizophora mucronata and R. apiculata as main planted species. Other species are Lunmitzera racemosa, Excoecaria agallocha, Bruguiera gymnorhiza and Avicennia which grow naturally. SPOT data were digitally analysed using Didactim software. A color composite image was analysed. A barycentric supervised classification and textural analysis were applie.d. As an intermediate data, infrared color aerial photographs at 1130,000 (1981) were interpreted manually. At least two mangrove types of mangrove could be identified from the SPOT image. Dense mangrove was found in Petak 7, Petak 8, Petak 9 and Petak 12. In the other Petaks, mangrove were less than 20% of their surface. Mangrove of Rhizophora in 26 Petaks covered 290 Ha only.
Spatially distributed snow depth, bulk density, and snow water equivalent from ground-based and airborne sensor integration at Grand Mesa, Colorado, USA

Spaceborne remote sensing of snow currently enables landscape-scale snow covered area, but estimating snow mass in the mountains remains a major challenge from space. Airborne LiDAR can retrieve snow depth, and some promising results have recently been shown from spaceborne platforms, yet density estimates are required to convert snow depth to snow water 15 equivalent (SWE). However, the retrieval of snow bulk density remains unsolved, and limited data is available to evaluate model estimates of density in mountainous terrain. Knowledge of the spatial patterns and predictors of density is critical for accurate assessment of SWE and essential snow physics, such as energy balance and mechanics related to hazards and over-snow mobility. Toward the goal of landscape-scale retrievals of snow density, we estimated bulk density and length-scale variability by combining ground-penetrating radar (GPR) two-way travel-time observations and airborne LiDAR snow depths 20 collected during the mid-winter NASA SnowEx 2020 campaign at Grand Mesa, Colorado, USA. Key advancements of our approach include an automated layer picking method that leverages co-and cross-polarization coherence and distributed LiDAR–GPR inferred bulk density with machine learning. The root-mean-square error between the distributed estimates is 12 cm for depth, 27 kg/m 3 for density, and 42 mm for SWE, and the median relative uncertainty in distributed SWE is 7 %. Wind, terrain, and vegetation interactions display corroborated controls on bulk density that show model and observation 25 agreement. The spatially continuous snow density and SWE estimated over approximately 16 km 2 represents the next step towards broad-scale SWE retrieval.
Classification of land cover using optimized neural nets on SPOT data

Often papers, which compare the performance of neural net classifiers with traditional classifiers, tend to de-emphasize the importance of the network configuration. This paper presents the results of experiments with the use of neural nets for land-cover classification in a SPOT satellite image. Segments in the image are described by textural features calculated from gray-level difference statistics. The segments are found using an algorithm based on iterative use of adaptive noise filtering and region growing. An artificial neural net, a backpropagation net with two hidden layers (often referred to as a three-layer perceptron), is used to classify the segments. A variety of segment sizes are generated by the region growing procedure, and some of these are obviously too small for a textural description.
A New Two-Dimensional Physical Basis for the Complementary Relation between Terrestrial and Pan Evaporation

Abstract Archived global measurements of water loss from evaporation pans constitute an important indirect measure of evaporative flux. Historical data from evaporation pans shows a decreasing trend over the last half century, but the relationship between pan evaporation and moisture-limited terrestrial evaporation is complex, leading to ambiguities in the interpretation of these data. Under energy-limited conditions, pan evaporation Epan and moisture-limited terrestrial evaporation E increase or decrease together, whereas in moisture-limited conditions these fluxes form a complementary relation (CR) in which increases in one rate accompany decreases in the other rate. This has led to debate about the meaning of the observed trends in the context of changing climate. Here a two-dimensional numerical model of a wet pan in a drying landscape is used to demonstrate that, over a wide range of realistic atmospheric and surface conditions, the influence that changes in E have on Epan 1) are complementary and li.
Global analysis of the mammalian RNA degradome reveals widespread miRNA-dependent and miRNA-independent endonucleolytic cleavage

The Ago2 component of the RNA-induced silencing complex (RISC) is an endonuclease that cleaves mRNAs that base pair with high complementarity to RISC-bound microRNAs. Many examples of such direct cleavage have been identified in plants, but not in vertebrates, despite the conservation of catalytic capacity in vertebrate Ago2. We performed parallel analysis of RNA ends (PAREs), a deep sequencing approach that identifies 5′-phosphorylated, polyadenylated RNAs, to detect potential microRNA-directed mRNA cleavages in mouse embryo and adult tissues. We found that numerous mRNAs are potentially targeted for cleavage by endogenous microRNAs, but at very low levels relative to the mRNA abundance, apart from miR-151-5p-guided cleavage of the N4BP1 mRNA. We also find numerous examples of non-miRNA-directed cleavage, including cleavage of a group of mRNAs within a CA-repeat consensus sequence. The PARE analysis also identified many examples of adenylated small non-coding RNAs, including microRNAs, tRNA processing intermediates and various other small RNAs, consistent with adenylation being part of a widespread proof-reading and/or degradation pathway for small RNAs.
Northern Eurasian Heat Waves and Droughts

AbstractThis article reviews the understanding of the characteristics and causes of northern Eurasian summertime heat waves and droughts. Additional insights into the nature of temperature and precipitation variability in Eurasia on monthly to decadal time scales and into the causes and predictability of the most extreme events are gained from the latest generation of reanalyses and from supplemental simulations with the NASA Goddard Earth Observing System model, version 5 (GEOS-5). Key new results are 1) the identification of the important role of summertime stationary Rossby waves in the development of the leading patterns of monthly Eurasian surface temperature and precipitation variability (including the development of extreme events such as the 2010 Russian heat wave); 2) an assessment of the mean temperature and precipitation changes that have occurred over northern Eurasia in the last three decades and their connections to decadal variability and global trends in SST; and 3) the quantification (via.
Reply to Wernick et al.: Global scale quantification of forest change

Our results, reported in Hansen et al. (1) in a recent issue of PNAS, illustrate the value of earth observation data sets in generating internally consistent quantifications of land cover change, specifically, gross forest cover loss at the global scale. In that article, we state that our results are limited to this dynamic and that a more complete characterization of forest change would include forest cover gain and the proximate drivers of change. Wernick et al. (2) take issue with (i) our purported dismissal of other data and findings and (ii) the lack of reforestation/carbon uptake analyses. Concerning existing global data sets on forest extent and change, the issues regarding definitions and the difficulty in producing global scale syntheses is well described by others and referenced in our paper (3, 4). We believe that improved consistency in both definitions and methods is needed to advance global forest monitoring. Our results are a step in that direction and illustrate the value of deriving internally consistent and directly comparable results at the global scale. Our study does not replace or supersede other results, and we do not present our result as “the only one based on sound data. ” Our results are unique and limited to the gross forest cover loss dynamic.
Object component models using Gabor filters for visual recognition

The primate visual system is extremely successful and efficient in the challenging task of recognizing objects in complex scenes. A key component of the primate visual system is a massive utilization of neuronal circuits located in the low-level visual cortex areas, with responses similar to Gabor functions. These functions have important properties for image analysis such as selectivity to orientation, scale and frequency and being specially suited to characterize image texture. In this thesis we explore the properties of Gabor functions in the context of componentbased object recognition. Current component-based object recognition approaches represent objects as constellation of sub-parts, dividing the problem in three stages: interest region selection, image region description and, eventually, the recognition step. We introduce novel methods using Gabor filters for interest point selection and image region description. Performance is evaluated with state-of-the-art object recognition architectures. Regarding the selection of interest points, we define a new top-down saliency function. We encode the appearance of object components in terms of Gabor filter responses to build the saliency function. This saliency function computes a wavelength profile for every component, being effective in filtering out clutter and noisy features. The aim of this function is to reduce the number of candidates for posterior analysis, but maintaining high recall rates. Once the points of interest have been detected, we propose region descriptors with rich and efficient matching representations that explore the full set of parameters of Gabor filters. Local maxima of the filter energy response is the criterion to define two types of descriptors: a feature vector formed by Gabor filter responses that are chosen specifically for each object component and an alternative way to compute the SIFT descriptor. We perform extensive tests in real scenarios, to show experimentally that our models for interest point selection and local descriptor computation are well suited for component-based object recognition. Results show that approaches based on Gabor filter responses outperform state-of-the-art approaches in several aspects of the object recognition problem.
Building Stronger Economic Institutions in Developing Countries, the Role of FDI

Foreign Direct Investment flows to developing economies have increased significantly over the last decades, bringing about important changes in the developing world. This paper is interested in the institutional aspect of these changes, a dimen-sion weakly investigated in the development literature. More precisely, it explores how the quality of economic institutions in developing countries responds to changes in FDI inflows. The results, based on extensive data on FDI for a large sample of developing countries over the period 1990-2009, show that economic institutions improve in countries with larger FDI flows. On average, a 10-point increase in FDI inflows as a percent of GDP is associated with a 0.9-point increase in the quality of economic institutions. The results also show that this effect is driven by FDI flows from developed economies while no significant link is detected for FDI from developing economies. Furthermore, they indicate that the positive institutional impact of total FDI is likely to be mitigated in countries where the natural resources sector represents a major driver of FDI. The findings suggest that the quality of the institutions in FDI origin countries matters in the FDI/economic institutions relationship in the developing world. Overall, the results are robust to a series of sensitivity tests including the introduction of additional control variables, the exclusion of outliers, the test of income group and regional effects, and heterogeneity analysis based on the level of institutional development of the origin countries.
Meteor-3 Total Ozone Mapping Spectrometer (TOMS) Data Products User's Guide

This document is a guide to the data products derived from the measurements made by the Total Ozone Mapping Spectrometer (TOMS) experiment aboard the Meteor-3 satellite, and processed by the National Aeronautics and Space administration (NASA). It discusses the calibration of the instrument, the algorithm used to derive ozone values from the measurements, uncertainties in the data, and the organization of the data products. The data begins August 22, 1991 and ends December 28, 1994. These data are archived at the Goddard Space Flight Center (GSFC) Distributed Active Archive Center (DAAC). Meeor-3 data have been processed independently by the Central Aerological Observatory (CAO) of the Russian State Committee on Hydrometeorology (Hydromet); that processing and its products are not discussed in this document.
Global Characteristics of Ocean Variability Estimated from Regional TOPEX/POSEIDON Altimeter Measurements

Abstract Three years of altimetric data from the TOPEX/POSEIDON spacecraft have been used to study characteristics of eddy variability over the World Ocean. The nature of the variability and its spatial structure are characterized in terms of the geographical distribution of eddy energy, as simple approximations of observed regional frequency and wavenumber spectra, and in terms of associated eddy time and space scales of sea surface height (SSH) variability and geostrophic velocity. Emphasis is put on summarizing characteristics typical for dynamically distinct regions of the World Ocean. This effort results in an attempt to describe the observed ocean variability in terms of universal spectral relations that depend only on few mean flow parameters such as the first-mode Rossby radius of deformation. Regional peculiarities follow naturally as deviations from the fundamental frequency and wavenumber spectra presented here. Frequency spectra of both variables can be summarized by three basic types represen.
Data analysis at scale

Abstract My research focuses on methods to analyze and mine large datasets as well as their practical realizations and applications. The key question of interest to me is: How can we effectively and efficiently distill useful information from large, complex, and potentially noisy datasets? To approach this question, we are developing systems for scalable data analysis and data mining, for working with incomplete and noisy data, for data-intensive optimization, as well as for extracting structured information from natural-language text. This article highlights some of my work in these areas.
notoginsenoside r1 attenuates high glucose-induced endothelial damage in rat retinal capillary endothelial cells by modulating the intracellular redox state

: The aim of this study was to examine whether Notoginsenoside R1 (NR1) attenuates high glucose-induced cell damage in rat retinal capillary endothelial cells (RCECs) and to explore the mechanisms involved. The exposure of rat RCECs to high concentration of glucose (30 mM) for 72 h led to significant cytotoxicity, including decreased cell viability, reduced mitochondrial DNA copy number, increased lactate dehydrogenase release and elevated apoptosis. NR1, when present in the culture medium, markedly attenuated the high glucose-induced cytotoxicity in rat RCECs. Moreover, high glucose also induced a significant increase in intra-cellular reactive oxygen species and subsequently increased the activity of NADPH oxidase and poly-ADP (ribose) polymerase, whereas the activity of catalase decreased. The addition of NR1 to the medium significantly reduced the generation of reactive oxygen species, inhibited NADPH oxidase and poly-ADP (ribose) polymerase activities and increased catalase activity in RCECs, accompanied by a reduced cellular nitrotyrosine level. To explore the underlying mechanisms involved, the cellular redox status was monitored. Both the cellular NAD + and NADPH levels decreased significantly in high glucose medium, which resulted in a marked decrease in the NAD + /NADH and NADPH/NADP + ratios. High glucose stimulation also enhanced the accumulation of GSSG, maintaining the GSH/GSSG ratio lower than that in the control group with 5.5 mM glucose. When treated with NR1, the cellular NAD + , NADPH and GSH concentrations increased, and the ratios of NAD + /NADH, NADPH/NADP + and GSH/ GSSG increased, similar to the control group. These results demonstrate that NR1 attenuates high glucose-induced cell damage in RCECs. Therefore, NR1 may exert its protective effects via mechanisms that involve changes in the cellular redox state.
Characterization of model polar stratospheric cloud films using Fourier transform infrared spectroscopy and temperature programmed desorption

This study combines Fourier transform infrared (FTIR) spectroscopy and temperature programmed desorption (TPD) measurements of nitric-acid/ice films representative of type I polar stratospheric clouds (PSCs). Using this combination of techniques, we are able to correlate the FTIR spectra with measurements of the film stoichiometry. The results confirm the assignments for amorphous nitric-acid/ice films and for crystalline nitric acid trihydrate (NAT), dihydrate, and monohydrate proposed by Ritzhaupt and Devlin (1991). In addition to these films, we observe a new high temperature nitric-acid/ice film which we attribute to a more stable structure of NAT with fewer defects. When low temperature crystalline NAT is heated, such as during TPD or slow annealing, the IR absorption spectrum irreversibly changes around −88° to −75°C. Future IR absorption measurements of PSCs in the atmosphere should be compared with IR spectra of both amorphous and crystalline nitric acid/ice, including both forms of NAT.
Screen-space Percentage-Closer Soft Shadows

We present an algorithm for computing Percentage-Closer Soft Shadows inside a screen-space rendering loop. Our algorithm is faster than traditional soft shadows based on percentage closer filtering, while providing soft shadows of similar visual quality. It combines naturally with a deferred shading pipeline, making it an ideal choice for video games. This algorithm is not only faster, but allows the use of larger shadow maps without dramatically affecting the rendering speed.
Real-Parameter Black-Box Optimization Benchmarking 2009: Experimental Setup

Quantifying and comparing performance of optimization algorithms is one important aspect of research in search and optimization. However, this task turns out to be tedious and difficult to realize even in the single-objective case -- at least if one is willing to accomplish it in a scientifically decent and rigorous way. The BBOB 2009 workshop will furnish most of this tedious task for its participants: (1) choice and implementation of a well-motivated single-objective benchmark function testbed, (2) design of an experimental set-up, (3) generation of data output for (4) post-processing and presentation of the results in graphs and tables. What remains to be done for the participants is to allocate CPU-time, run their favorite black-box real-parameter optimizer in a few dimensions a few hundreds of times and execute the provided post-processing script afterwards. Here, the experimental procedure and data formats are thoroughly defined and motivated and the data presentation is touched on.
Cache aware mapping of streaming apllications on a multiprocessor system-on-chip

Ef(cid:2)cient use of the memory hierarchy is critical for achieving high performance in a multiprocessor system-on-chip. An external memory that is shared between processors is a bottleneck in current and future systems. Cache misses and a large cache miss penalty contribute to a low processor utilisation. In this paper, we describe a novel cache optimisation technique to reduce instruction and data cache misses for streaming applications. The instruction and data locality are improved by executing a task multiple times before moving to the next task. Furthermore, we introduce a data(cid:3)ow model that is used to trade-off the number of cache misses against end-to-end latency and memory usage. For our industrial application, which is a Digital Radio Mondiale receiver, the number of cache misses is reduced with a factor 4.2.