Miracle-dz/UniFAR-FTUs huggingface dataset:
Extensive DNA End Processing by Exo1 and Sgs1 Inhibits Break-Induced Replication

Homology-dependent repair of DNA double-strand breaks (DSBs) by gene conversion involves short tracts of DNA synthesis and limited loss of heterozygosity (LOH). For DSBs that present only one end, repair occurs by invasion into a homologous sequence followed by replication to the end of the chromosome resulting in extensive LOH, a process called break-induced replication (BIR). We developed a BIR assay in Saccharomyces cerevisiae consisting of a plasmid with a telomere seeding sequence separated from sequence homologous to chromosome III by an I-SceI endonuclease recognition site. Following cleavage of the plasmid by I-SceI in vivo, de novo telomere synthesis occurs at one end of the vector, and the other end invades at the homologous sequence on chromosome III and initiates replication to the end of the chromosome to generate a stable chromosome fragment (CF). BIR was infrequent in wild-type cells due to degradation of the linearized vector. However, in the exo1Δ sgs1Δ mutant, which is defective in the 5′-3′ resection of DSBs, the frequency of BIR was increased by 39-fold. Extension of the invading end of the plasmid was detected by physical analysis two hours after induction of the I-SceI endonuclease in the wild-type exo1Δ, sgs1Δ, and exo1Δ sgs1Δ mutants, but fully repaired products were only visible in the exo1Δ sgs1Δ mutant. The inhibitory effect of resection was less in a plasmid-chromosome gene conversion assay, compared to BIR, and products were detected by physical assay in the wild-type strain. The rare chromosome rearrangements due to BIR template switching at repeated sequences were increased in the exo1Δ sgs1Δ mutant, suggesting that reduced resection can decrease the fidelity of homologous recombination.
Image simulation for automatic license plate recognition

Automatic license plate recognition (ALPR) is an important capability for traffic surveillance applications, including toll monitoring and detection of different types of traffic violations. ALPR is a multi-stage process comprising plate localization, character segmentation, optical character recognition (OCR), and identification of originating jurisdiction (i.e. state or province). Training of an ALPR system for a new jurisdiction typically involves gathering vast amounts of license plate images and associated ground truth data, followed by iterative tuning and optimization of the ALPR algorithms. The substantial time and effort required to train and optimize the ALPR system can result in excessive operational cost and overhead. In this paper we propose a framework to create an artificial set of license plate images for accelerated training and optimization of ALPR algorithms. The framework comprises two steps: the synthesis of license plate images according to the design and layout for a jurisdiction of interest; and the modeling of imaging transformations and distortions typically encountered in the image capture process. Distortion parameters are estimated by measurements of real plate images. The simulation methodology is successfully demonstrated for training of OCR.
Fusing range and intensity images for mobile robot localization

We present the two-dimensional (2-D) version of the symmetries and perturbation model (SPmodel), a probabilistic representation model and an extended Kalman filter integration mechanism for uncertain geometric information that is suitable for sensor fusion and integration in multisensor systems. We apply the SPmodel to the problem of location estimation in indoor mobile robotics, experimenting with the mobile robot MACROBE. We have chosen two types of complementary sensory information: (1) range images; (2) intensity images; obtained from a laser sensor. Results of these experiments show that fusing simple and computationally inexpensive sensory information can allow a mobile robot to precisely locate itself. They also demonstrate the generality of the proposed fusion and integration mechanism.
A Novel Index Combining Diastolic and Systolic Tissue Doppler Parameters for Prediction of Atrial Fibrillation Recurrence

Identification of patients at risk for atrial fibrillation (AF) recurrence with using simple and objective parameters may be helpful in tailoring the treatment. In this study, we investigated whether E/(Ea×Sa) and Ea/(Aa×Sa) could be a predictor of AF recurrence after cardioversion. (E = early diastolic transmitral velocity, Ea = early diastolic mitral annular velocity, Aa = late diastolic mitral annular velocity, Sa = systolic mitral annular velocity).
Quality Perception of Simplified Models: NSA vs. QSLIM

Quality perception of simplified models is an important aspect for several applications. But, it is normally evaluated only based on the analysis of geometrical errors of the simplified models. However, the analysis of geometrical errors is not enough to evaluate the quality of the simplified models. The quality of the simplified models and the execution times are the main aspects that distinguish the simplification algorithms. These algorithms are of great interest in a variety of areas, since they allow the replacement of large models by approximations with far fewer cells for manipulation and visualization purposes. This paper presents a comparison between two simplification algorithms, NSA and Qslim, and shows the difference between geometrical and graphical quality of the models. The comparison of results was made using the PolyMeCo tool, which enables the analysis and comparison of meshes by providing an environment where several visualization options and metrics are available and can be used in a coordinated way.
ReactionPredictor: Prediction of Complex Chemical Reactions at the Mechanistic Level Using Machine Learning

Proposing reasonable mechanisms and predicting the course of chemical reactions is important to the practice of organic chemistry. Approaches to reaction prediction have historically used obfuscating representations and manually encoded patterns or rules. Here we present ReactionPredictor, a machine learning approach to reaction prediction that models elementary, mechanistic reactions as interactions between approximate molecular orbitals (MOs). A training data set of productive reactions known to occur at reasonable rates and yields and verified by inclusion in the literature or textbooks is derived from an existing rule-based system and expanded upon with manual curation from graduate level textbooks. Using this training data set of complex polar, hypervalent, radical, and pericyclic reactions, a two-stage machine learning prediction framework is trained and validated. In the first stage, filtering models trained at the level of individual MOs are used to reduce the space of possible reactions to consider. In the second stage, ranking models over the filtered space of possible reactions are used to order the reactions such that the productive reactions are the top ranked. The resulting model, ReactionPredictor, perfectly ranks polar reactions 78.1% of the time and recovers all productive reactions 95.7% of the time when allowing for small numbers of errors. Pericyclic and radical reactions are perfectly ranked 85.8% and 77.0% of the time, respectively, rising to >93% recovery for both reaction types with a small number of allowed errors. Decisions about which of the polar, pericyclic, or radical reaction type ranking models to use can be made with >99% accuracy. Finally, for multistep reaction pathways, we implement the first mechanistic pathway predictor using constrained tree-search to discover a set of reasonable mechanistic steps from given reactants to given products. Webserver implementations of both the single step and pathway versions of ReactionPredictor are available via the chemoinformatics portal http://cdb.ics. uci.edu/.
Distinguishing ischemic from non-ischemic ST changes: the Physionet/Computers in Cardiology Challenge 2003

Accurate diagnosis of myocardial ischemia during activities of daily living, if possible, would provide immediate and substantial benefits to affected subjects, by reducing the time needed to determine and evaluate therapeutic interventions intended to reduce or eliminate transient ischemia. Although ST changes provide a sensitive indicator of ischemia, a variety of non-ischemic mechanisms can also result in ST changes, so that ECG-based diagnosis of ischemia is regarded as non-specific and unreliable. It may be possible, by study of the dynamics of ST changes, to improve the specificity of ECG criteria consistent with ischemia. The fourth annual PhysioNet/Computers in Cardiology Challenge encouraged participants to develop and evaluate methods for distinguishing ischemic and non-ischemic ST changes using a standard, meticulously annotated data set. The training data provided to participants, and the algorithms they developed, are available at http://-www.physionet. org/challenge/2003/.
An effective clustering approach to web query log anonymization

Web query log data contain information useful to research; however, release of such data can re-identify the search engine users issuing the queries. These privacy concerns go far beyond removing explicitly identifying information such as name and address, since non-identifying personal data can be combined with publicly available information to pinpoint to an individual. In this work we model web query logs as unstructured transaction data and present a novel transaction anonymization technique based on clustering and generalization techniques to achieve the k-anonymity privacy. We conduct extensive experiments on the AOL query log data. Our results show that this method results in a higher data utility compared to the state-of-the-art transaction anonymization methods.
Sensing characteristics of the gold-silver alloy waveguided metallic photonic crystals

The waveguided metallic photonic crystal biosensor based on gold-silver alloy material is expected to achieve better sensing sensitivity than the same structure of pure gold. By using the gold-silver alloy nanoparticles as “building block”, we successfully assemble one-dimensional waveguided metallic photonic crystals through a solution processible method. This is a simple and low cost method to fabricate one or two dimensional metallic crystals in large area. The sensitivity of the biosensor based on the gold-silver alloy waveguided metallic photonic crystal is 2.5 times that of the same structure made by pure gold. The gold-silver alloy nanoparticles assembled waveguided metallic photonic crystals exhibits potential application in biosensing due to its low-cost and simple testing methods.
Promoting Access to White Rose Research Papers Thermal and Chemical Unfolding and Refolding of a Eukaryotic Sodium Channel

(2009) Thermal and chemical unfolding and refolding of a eukaryotic sodium channel. 1 Summary Voltage-gated sodium channels are dynamic membrane proteins essential for signaling in nervous and muscular systems. They undergo substantial conformational changes associated with the closed, open and inactivated states. However, little information is available regarding their conformational stability. In this study circular dichroism spectroscopy was used to investigate the changes in secondary structure accompanying chemical and thermal denaturation of detergent-solubilised sodium channels isolated from Electrophorus electricus electroplax. The proteins appear to be remarkably resistant to either type of treatment, with " denatured " channels, retaining significant helical secondary structure even at 77 o C or in 10% SDS. Further retention of helical secondary structure at high temperature was observed in the presence of the channel-blocking tetrodotoxin. It was possible to refold the thermally-denatured (but not chemically-denatured) channels in vitro. The correctly refolded channels were capable of undergoing the toxin-induced conformational change indicative of ligand binding. In addition, flux measurements in liposomes showed that the thermally-denatured (but not chemically-denatured) proteins were able to re-adopt native, active conformations. These studies suggest that whilst sodium channels must be sufficiently flexible to undergo major conformational changes during their functional cycle, the proteins are highly resistant to unfolding, a feature that is important for maintaining structural integrity during dynamic processes.
Mind bomb-1 Is Essential for Intraembryonic Hematopoiesis in the Aortic Endothelium and the Subaortic Patches

ABSTRACT Intraembryonic hematopoiesis occurs at two different sites, the floor of the aorta and subaortic patches (SAPs) of the para-aortic splanchnopleura (P-Sp)/aorta-gonad-mesonephros (AGM) region. Notch1 and RBP-jκ are critical for the specification of hematopoietic stem cells (HSCs) in Notch signal-receiving cells. However, the mechanism by which Notch signaling is triggered from the Notch signal-sending cells to support embryonic hematopoiesis remains to be determined. We previously reported that Mind bomb-1 (Mib1) regulates Notch ligands in the Notch signal-sending cells (B. K. Koo, M. J. Yoon, K. J. Yoon, S. K. Im, Y. Y. Kim, C. H. Kim, P. G. Suh, Y. N. Jan, and Y. Y. Kong, PLoS ONE 2:e1221, 2007). Here, we show that intraembryonic hematopoietic progenitors were absent in the P-Sp of Mib1−/− embryos, whereas they were partly preserved in the Tie2-cre; Mib1f/f P-Sps, suggesting that Mib1 plays a role in the endothelium and the SAPs. Interestingly, dll1 and dll4/Jag1 are expressed in the SAPs and the endothelium of the AGM, respectively, where mib1 is detected. Indeed, Notch signaling was activated in the nascent HSCs at both sites. In the P-Sp explant culture, the overexpression of Dll1 in OP9 stromal cells rescued the failed production of hematopoietic progenitors in the Mib1−/− P-Sp, while its activity was abolished by Mib1 knockdown. These results suggest that Mib1 is important for intraembryonic hematopoiesis not only in the aortic endothelium but also in the SAPs.
Multi-guarded safe zone: An effective technique to monitor moving circular range queries

Given a positive value r, a circular range query returns the objects that lie within the distance r of the query location. In this paper, we study the circular range queries that continuously change their locations. We present an efficient and effective technique to monitor such moving range queries by utilising the concept of a safe zone. The safe zone of a query is the area with a property that while the query remains inside it, the results of the query remain unchanged. Hence, the query does not need to be re-evaluated unless it leaves the safe zone. The shape of the safe zone is defined by the so-called guard objects. The cost of checking whether a query lies in the safe zone takes k distance computations, where k is the number of the guard objects. Our contributions are as follows. 1) We propose a technique based on powerful pruning rules and a unique access order which efficiently computes the safe zone and minimizes the I/O cost. 2) To show the effectiveness of the safe zone, we theoretically evaluate the probability that a query leaves the safe zone within one time unit and the expected distance a query moves before it leaves the safe zone. Additionally, for the queries that have diameter of the safe zone less than its expected value multiplied by a constant, we also give an upper bound on the expected number of guard objects. This upper bound turns out to be a constant, that is, it does not depend either on the radius r of the query or the density of the objects. The theoretical analysis is verified by extensive experiments. 3) Our thorough experimental study demonstrates that our proposed approach is close to optimal and is an order of magnitude faster than a naïve algorithm.
Serum albumin fragmentation in end-stage renal disease patients – a pilot study

Abstract Background: The goal of this study was to detect modification in the expression of plasma proteins and/or post-translational modifications of their structure in patients with end stage renal disease. Methods: Serum samples from 19 adult patients treated by maintenance hemodialysis (MHD) were analyzed in comparison to sera from six healthy controls using sodium dodecylsulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and two-dimensional electrophoresis (2DE). Spots of interest were identified by mass spectrometry analysis. In addition, the 2DE maps were incubated with a human anti-albumin polyclonal antibody. Results: SDS-PAGE gels, 2DE maps and matrix-assisted laser desorption/ionization time of flight analysis indicated over-expression of low-molecular weight proteins (LMWP) in sera from patients. Unexpectedly, another 15 spots with estimated Mr of 12.5–29 kDa from the 2DE maps of six patients were identified as fragments of albumin. 2D immunoblotting of sera from 12 other patients detected numerous albumin fragments. Conclusions: These results indicate that in addition to increased expression of LMWP, a relevant amount of albumin fragments are detectable in the serum of patients undergoing MHD. Uremia appears to facilitate the fragmentation of albumin and/or the retention of albumin fragments in blood. Clin Chem Lab Med 2009;47:1373–9.
Fast connected components algorithms for the EREW PRAM

We present fast and efficient parallel algorithms for finding the connected components of an undirected graph. These algorithms run on the exclusive-read, exclusive-write (EREW) PRAM. On a graph with n vertices and m edges, our randomized algorithm runs in O(log n) time using $(m+n^{1+\epsilon})/\log n$ EREW processors (for any fixed $\epsilon>0$). A variant uses (m+n)/log n processors and runs in O(log n log log n) time. A deterministic version of the algorithm runs in $O(\log^{1.5}n)$ time using m+n EREW processors.
Acute respiratory distress syndrome in children: physiology and management

Purpose of review The present review seeks to review the pathophysiologic processes that underlie the development of acute respiratory distress syndrome (ARDS) in children. The review intends to provide the physiologic foundation for the treatment strategies that are associated with the most optimal outcome. Recent findings In infants and children, ARDS remains a significant cause of morbidity and mortality. Although any infant or child can develop ARDS, children who have experienced trauma, pneumonia, aspiration, or immune compromise are at increased risk. Data indicate that adoption of an open-lung ventilation strategy, characterized by sufficient positive end-expiratory pressure to avoid atelectasis, a tidal volume that is limited to less than 5–7 cc/kg per breath and a plateau pressure of 30 cm of water or less provides the greatest likelihood of survival and minimizes lung injury. The relative benefits of strategies such as high frequency oscillatory ventilation, surfactant replacement therapy and inhaled nitric oxide are considered. Summary ARDS remains a cause of significant mortality and morbidity in children. By employing sound physiologic principles, clinical outcomes can be optimized.
Workspace analysis and optimal design of a 3-leg 6-DOF parallel platform mechanism

A new class of six-degree-of-freedom (DOFs) spatial parallel platform mechanism is considered in this paper. The architecture consists of a mobile platform connected to the base by three identical kinematic chains using five-bar linkages. Recent investigations showed that parallel mechanisms with such a topology for the legs can be efficiently statically balanced using only light elastic elements. This paper follows up with a workspace analysis and optimization of the design of that parallel mechanism. More specifically, considering a possible industrial application of the architecture as a positioning and orienting device of heavy loads, an optimization procedure for the maximization of the volume of the three-dimensional (3-D) constant-orientation workspace of the mechanism is first presented. As the mechanism could also have great potential as a motion base for flight simulators, we develop here a discretization method for the computation and graphical representation of a new workspace with coupled translational and rotational DOFs. This workspace can be defined as the 3-D space which can be obtained when generalized coordinates x,y and torsion angle /spl psi/ in the tilt-and-torsion angles parametrization are constant. A second procedure is then presented for the maximization of the volume of this second subset of the complete workspace. For both approaches, our purpose is to attempt an optimal design of the mechanism by maximizing the volume of the associated 3-D Cartesian region that is free of critical singularity loci.
A String Constraint Solver for Detecting Web Application Vulnerability

Given the bytecode of a software system, is it possible to automatically generate attack signatures that reveal it s vulnerabilities? A natural solution would be symbolically executing the target system and constructing constraints for matching path conditions and attack patterns. Clearly, the constraint solving technique is the key to the above research. This paper presents Simple Linear String Equation (SISE), a formalism for specifying constraints on strings. SISE uses finite state transducers to precisely model variou s regular replacement operations, which makes it applicable for analyzing text processing programs such as web applications. We present a recursive algorithm that computes the solution pool of a SISE. Given the solution pool, a concrete variable solution can be generated. The algorithm is implemented in a Java constraint solver called SUSHI, which is applied to security analysis of web applications.
A multiscale filter for noise reduction of low-dose cone beam projections

The Poisson or compound Poisson process governs the randomness of photon fluence in cone beam computed tomography (CBCT) imaging systems. The probability density function depends on the mean (noiseless) of the fluence at a certain detector. This dependence indicates the natural requirement of multiscale filters to smooth noise while preserving structures of the imaged object on the low-dose cone beam projection. In this work, we used a Gaussian filter, exp(−x2/2σf2) ? > as the multiscale filter to de-noise the low-dose cone beam projections. We analytically obtained the expression of σf ? >, which represents the scale of the filter, by minimizing local noise-to-signal ratio. We analytically derived the variance of residual noise from the Poisson or compound Poisson processes after Gaussian filtering. From the derived analytical form of the variance of residual noise, optimal σf2 ? > is proved to be proportional to the noiseless fluence and modulated by local structure strength expressed as the linear fitting error of the structure. A strategy was used to obtain the reliable linear fitting error: smoothing the projection along the longitudinal direction to calculate the linear fitting error along the lateral direction and vice versa. The performance of our multiscale filter was examined on low-dose cone beam projections of a Catphan phantom and a head-and-neck patient. After performing the filter on the Catphan phantom projections scanned with pulse time 4 ms, the number of visible line pairs was similar to that scanned with 16 ms, and the contrast-to-noise ratio of the inserts was higher than that scanned with 16 ms about 64% in average. For the simulated head-and-neck patient projections with pulse time 4 ms, the visibility of soft tissue structures in the patient was comparable to that scanned with 20 ms. The image processing took less than 0.5 s per projection with 1024 × 768 pixels.