Miracle-dz/UniFAR-FTUs huggingface dataset:
Rehospitalizations Following Primary Percutaneous Coronary Intervention in Patients With ST‐Elevation Myocardial Infarction: Results From a Multi‐Center Randomized Trial

Background Rehospitalizations (RHs) after ST‐elevation myocardial infarction carry a high economic burden and may deteriorate quality of life. Characterizing patients at higher risk may allow the design of preventive measures. We studied the frequency, reasons, and predictors for unplanned cardiac and noncardiac RHs in ST‐elevation myocardial infarction patients undergoing primary percutaneous coronary intervention. Methods and Results In this post‐hoc analysis of the COMFORTABLE AMI (Comparison of Biolimus Eluted From an Erodible Stent Coating With Bare Metal Stents in Acute ST‐Elevation Myocardial Infarction; NCT00962416) trial including 1137 patients, unplanned cardiac and noncardiac RHs occurred in 133 (11.7%) and in 79 patients (6.9%), respectively, at 1 year. The most frequent reasons for unplanned cardiac RHs were recurrent chest pain without evidence of ischemia (20.4%), recurrent chest pain with ischemia and coronary intervention (16.9%), and ischemic events (16.9%). Unplanned noncardiac RHs occurred most frequently attributed to bleeding (24.5%), infections (14.3%), and cancer (9.1%). On multivariate analysis, left ventricular ejection fraction (22% increase in the rate of RHs per 10% decrease; P=0.03) and angiographic myocardial infarction Syntax score (34% increase per 10‐point increase; P=0.01) were independent predictors of unplanned cardiac RHs. Age emerged as the only independent predictor of unplanned noncardiac RHs. Regional differences for unplanned cardiac RHs were observed. Conclusions Among ST‐elevation myocardial infarction patients undergoing primary percutaneous coronary intervention in the setting of a randomized, clinical trial, unplanned cardiac RHs occurred in 12% with recurrent chest pain being the foremost reason. Unplanned noncardiac RHs occurred in 7% with bleeding as the leading cause. Left ventricular ejection fraction and Syntax score were independent predictors of unplanned cardiac RHs and identified patient subgroups in need for improved secondary prevention. Clinical Trial Registration URL: http://www.clinicaltrials. gov. Unique identifier: NCT00962416.
Separation of sodium and calcium currents in the somatic membrane of mollusc neurones. With an Appendix by Yu A. Shakhovalov

1. Characteristics of the transmembrane ionic currents under controlled changes in ionic composition of extra‐ and intracellular medium were studied in isolated neurones from the ganglia of molluscs, Helix pomatia, Limnea stagnalis and Planorbis corneus. The neurones were investigated by a new technique which allows for dialysis of their interior and for clamping of the potential at the surface membrane without using micro‐electrodes.
Automatic Identification of Locative Expressions from Social Media Text: A Comparative Analysis

With the proliferation of smartphones and the increasing popularity of social media, people have developed habits of posting not only their thoughts and opinions, but also content concerning their whereabouts. On such highly-interactive yet informal social media platforms, people make heavy use of informal language, including when it comes to locative expressions. Such usage inhibits the ability of traditional Natural Language Processing approaches to retrieve geospatial information from social media text. In this research, we: (1) develop a medium-scale corpus of "locative expressions" derived from a variety of social media sources; (2) benchmark the performance of a range of geoparsers over the corpus, with the finding that even the best-performing systems are substantially lacking; and (3) carry out extensive error analysis to suggest ways of improving the accuracy and robustness of geoparsers.
Engineering sulfur storage in maize seed proteins without apparent yield loss

Significance Poultry feed is usually prepared as a corn–soybean mixture. Because the only essential sulfur amino acid missing in this mixture is methionine, it is chemically synthesized and added separately, increasing the cost of major food supply. It appears to be difficult to circumvent the regulatory aspects of sulfur metabolism, which is controlled at many levels, without damage to plant growth. By using tissue-specific promoters to express a bacterial enzyme that increases the efficiency of assimilative sulfate reduction, seed methionine accumulation can be increased without the concomitant accumulation of toxic metabolites. We show that even in maize inbred lines with repressed seed methionine levels, sink strength can be increased to the benefit of feed consumption efficiency in chicks. Sulfur assimilation may limit the pool of methionine and cysteine available for incorporation into zeins, the major seed storage proteins in maize. This hypothesis was tested by producing transgenic maize with deregulated sulfate reduction capacity achieved through leaf-specific expression of the Escherichia coli enzyme 3′-phosphoadenosine-5′-phosphosulfate reductase (EcPAPR) that resulted in higher methionine accumulation in seeds. The transgenic kernels have higher expression of the methionine-rich 10-kDa δ-zein and total protein sulfur without reduction of other zeins. This overall increase in the expression of the S-rich zeins describes a facet of regulation of these proteins under enhanced sulfur assimilation. Transgenic line PE5 accumulates 57.6% more kernel methionine than the high-methionine inbred line B101. In feeding trials with chicks, PE5 maize promotes significant weight gain compared with nontransgenic kernels. Therefore, increased source strength can improve the nutritional value of maize without apparent yield loss and may significantly reduce the cost of feed supplementation.
Modeling physical capabilities of humanoid agents using motion capture data

In this paper we demonstrate a method for fine-grained modeling of a synthetic agentýs physical capabilities ¿ running, jumping, sneaking, and other modes of movement. Using motion capture data acquired from human subjects, we extract a motion graph and construct a cost map for the space of agent actions. We show how a planner can incorporate this cost model into the planning process to select between equivalent goal-achieving plans. We explore the utility of our model in three different capacities: 1) modeling other agents in the environment; 2) representing heterogeneous agents with different physical capabilities; 3) modeling agent physical states (e.g., wounded or tired agents). This technique can be incorporated into applications where human-like, high-fidelity physical models are important to the agentsý reasoning process, such as virtual training environments.
Optimal LED selection for multispectral lighting reproduction

We demonstrate the sufficiency of using as few as five LEDs of distinct spectra for multispectral lighting reproduction and solve for the optimal set of five from 11 such commercially available LEDs. We leverage published spectral reflectance, illuminant, and camera spectral sensitivity datasets to show that two approaches of lighting reproduction, matching illuminant spectra directly and matching material color appearance observed by one or more cameras or a human observer, yield the same LED selections. Our proposed optimal set of five LEDs includes red, green, and blue with narrow emission spectra, along with white and amber with broader spectra.
Evidence for Evolution or Bias in Host Extinctions of Type 1a Supernovae at High Redshift

Type 1a supernova magnitudes conventionally include an additive parameter called the extinction coefficient. We find that the extinction coefficients of a popular "gold" set are well correlated with the deviation of magnitudes from Hubble diagrams. If the effect is due to bias, extinctions have been overestimated, which makes supernovas appear more dim. The statistical significance of the extinction-acceleration correlation has a random chance probability of less than one in a million. The hypothesis that extinction coefficients should be corrected empirically provides greatly improved fits to both accelerating and nonaccelerating models, with the independent feature of eliminating any significant correlation of residuals.
Mechanisms and Control of Protein Translation in the Kidney

Translational control of protein synthesis is critical for cell division, homeostasis and survival. Recent data indicate that dysregulation of protein synthesis that leads to either increased or decreased expression of specific proteins contributes to the manifestations of various kidney diseases. Most of the control of protein synthesis occurs in the first or initiation phase, which is also the most complicated. Following the initiation phase is the elongation phase where the peptide chain is formed. RNA transcripts are released from ribosomes after the termination phase. Transcripts can be translated in a cap-dependent or cap-independent manner. The mTOR (mammalian target of rapamycin) cascade regulates translation of most cap-dependent transcripts at the level of initiation and elongation, which represents 95% of total transcripts. During specific events (e.g. mitosis, stress cell survival) control of the less-common cap-independent transcripts occurs which allows the cell to adapt to the new state. Activation of stress kinases and inactivation of the mTOR pathway are at the center of this adaptive mechanism. Recent studies have elucidated the role of micro-RNAs (miRs) in controlling translation. miRs bind directly to specific transcripts and most often directly reduce translation; however, by targeting other positive or negative regulators of the pathways regulating protein synthesis they may indirectly affect synthetic levels of other transcripts. Several examples are described below in which these mechanisms are intertwined and act together to dysregulate protein synthesis in the diseased kidney.
Reconcilable differences: correcting medication errors at hospital admission and discharge

Background: Medication errors at the time of hospital admission and discharge are common and can lead to preventable adverse drug events. The objective of this study was to describe the potential impact of a medication reconciliation process to identify and rectify medication errors at the time of hospital admission and discharge. Methods: Sixty randomly selected patients were prospectively enrolled at the time of admission to a Canadian community hospital. At admission, patients’ medication orders were compared with pre-admission medication use based on medication vials and interviews with patients, caregivers, and/or outpatient healthcare providers. At discharge, pre-admission and in-patient medications were compared with discharge orders and written instructions. All variances were discussed with the prescribing physician and classified as intended or unintended; unintended variances were considered to be medication errors. An internist classified the clinical importance of each unintended variance. Results: Overall, 60% (95% CI 48 to 72) of patients had at least one unintended variance and 18% (95% CI 9 to 28) had at least one clinically important unintended variance. None of the variances had been detected by usual clinical practice before reconciliation was conducted. Of the 20 clinically important variances, 75% (95% CI 56 to 94) were intercepted by medication reconciliation before patients were harmed. Discussion: Unintended medication variances at the time of hospital admission and discharge are common and clinically important. The medication reconciliation process identified and addressed most of these unintended variances before harm occurred. In this small study, medication reconciliation was a useful method for identifying and rectifying medication errors at times of transition. Reconciliation warrants broader evaluation.
Active learning of Hybrid Extreme Rotation Forests for CTA image segmentation

This paper proposes a Hybrid Extreme Rotation Forest (HERF) classifier for segmentation of 3D Computed Tomography Angiography (CTA) following an Active Learning (AL) approach. The HERF is an ensemble of classifiers composed of Extreme Learning Machines (ELM) and Decision Trees. Training of the HERF includes optimal rotation of random partitions of the feature set aimed to increase diversity. AL follows an strategy of optimal sample selection in order to minimize the number of data samples needed to obtain a required accuracy degree. AL is pertinent for interactive learning processes where a human operator is required to select training samples to enhance the classifier in an iterative process, therefore labeling samples for training may be a time consuming and expensive process. CTA image segmentation is one of such processes, due to the variability in CTA images which hinders the generalization of classifiers trained on one dataset to new datasets. Following an AL strategy, the human operator is presented with a visual selection of pixels whose labeling would be most informative for the classifier. After adding those labeled pixels to the training data, the classifier is retrained. This iteration is repeated until image segmentation quality meets the required level. The approach is applied to the segmentation of the thrombus in CTA data of Abdominal Aortic Aneurysm (AAA) patients, showing that the structures of interest in CTA volume can be accurately segmented after a few iterations using a small data sample.
Experiential Perspective on Knowledge Management

INTRODUCTION The last few decades have seen a growing proportion of organizational wealth being represented by intangible assets, i.e., assets with value that cannot be measured in terms of any physical attribute. Management thinking, conditioned over centuries to extract the greatest value out of physical assets, has had to bring within its ambit the leveraging of these intangible assets in building the capabilities required to deliver superior products and solutions. The discipline of knowledge management (KM) was born and came to encompass the gamut of organizational processes, responsibilities, and systems directed toward the assimilation, dissemination, harvest, and reuse of knowledge. In simpler terms, KM is the answer to the question, " How can the organization update and use its knowledge more effectively? " (Kochikar, 2000). Some of the world's most successful organizations , be they corporate, academic, or government , invest considerably in KM. McKinsey & Co. spends at least 10% of revenues on managing knowledge. The World Bank's annual KM budget is $50 million. IBM has one of the oldest formal KM initiatives, dating back to 1994. Substantial benefits have been reported across industries. Johnson & Johnson has implemented KM for speeding up the FDA application process and reported savings of $30 million on one product alone (Berkman, 2001). British Petroleum has estimated savings of $400 million a year, while Chevron has discovered operational cost savings of $2.5 billion over 8 years (Infosys, 2002). Tufts University's school of medicine has used KM to 3206 Experiential Perspective on Knowledge Management integrate its curricula and has been hailed as a national model for medical education (Genusa, 2001). KM is, however, not an unmixed blessing , as Storey and Barnett (2000) noted. Each organization must fashion a KM strategy that takes cognizance of its unique competencies, aspirations, and business context. Infosys Technologies (NASDAQ: INFY) has conceived, developed, and deployed internally an elaborate architecture for KM that aims to empower every employee with the knowledge of every other employee. The company's success on the knowledge-sharing front has been affirmed by the fact that the company has been a Global MAKE (most admired knowledge enterprises) winner in 2003 (Chase, 2003) and Asia MAKE winner for 2002, 2003. Key elements of the KM architecture include the Knowledge Currency Unit scheme, a comprehensive mechanism for reward, recognition, and measurement of KM benefits; KShop, the corporate knowledge portal built in-house; and the knowledge hierarchy, a four-level taxonomy …
Clinical Resistance to STI-571 Cancer Therapy Caused by BCR-ABL Gene Mutation or Amplification

Clinical studies with the Abl tyrosine kinase inhibitor STI-571 in chronic myeloid leukemia demonstrate that many patients with advanced stage disease respond initially but then relapse. Through biochemical and molecular analysis of clinical material, we find that drug resistance is associated with the reactivation of BCR-ABL signal transduction in all cases examined. In six of nine patients, resistance was associated with a single amino acid substitution in a threonine residue of the Abl kinase domain known to form a critical hydrogen bond with the drug. This substitution of threonine with isoleucine was sufficient to confer STI-571 resistance in a reconstitution experiment. In three patients, resistance was associated with progressiveBCR-ABL gene amplification. These studies provide evidence that genetically complex cancers retain dependence on an initial oncogenic event and suggest a strategy for identifying inhibitors of STI-571 resistance.
Mycotoxin Analysis: New Proposals for Sample Treatment

Mycotoxins are toxic secondary metabolites produced by different fungi, with different chemical structures. Mycotoxins contaminate food, feed, or raw materials used in their production and cause diseases and disorders in humans and livestock. Because of their great variety of toxic effects and their extreme heat resistance, the presence of mycotoxins in food and feed is considered a high risk to human and animal health. In order to ensure food quality and health consumers, European legislation has set maximum contents of some mycotoxins in different matrices. However, there are still some food commodities susceptible to fungal contamination, which were not contemplated in this legislation. In this context, we have developed new analytical techniques for the multiclass determination of mycotoxins in a great variety of food commodities (some of them scarcely studied), such as cereals, pseudocereals, cereal syrups, nuts, edible seeds, and botanicals. Considering the latest technical developments, ultrahigh performance liquid chromatography coupled to tandem mass spectrometry has been chosen as an efficient, fast, and selective powerful analytical technique. In addition, alternative sample treatments based on emerging methodologies, such as dispersive liquid-liquid microextraction and QuEChERS, have been developed, which allow an increased efficiency and sample throughput, as well as reducing contaminant waste.
Swift: A Fast Dynamic Packet Filter

This paper presents Swift, a packet filter for high performance packet capture on commercial off-the-shelf hard-ware. The key features of Swift include (1) extremely low filter update latency for dynamic packet filtering, and (2) Gbps high-speed packet processing. Based on complex instruction set computer (CISC) instruction set architecture (ISA), Swift achieves the former with an instruction set design that avoids the need for compilation and security checking, and the latter by mainly utilizing SIMD (single instruction, multiple data). We implement Swift in the Linux 2.6 kernel for both i386 and x86_64 architectures. The Swift userspace library supports two sets of application programming interfaces (APIs): a BPF-friendly API for backward compatibility and an object oriented API for simplifying filter coding. We extensively evaluate the dynamic and static filtering performance of Swift on multiple machines with different hardware setups. We compare Swift with BPF (the BSD packet filter)--the de facto standard for packet filtering in modern operating systems--and hand-coded optimized C filters that are used for demonstrating possible performance gains. For dynamic filtering tasks, Swift is at least three orders of magnitude faster than BPF in terms of filter update latency. For static filtering tasks, Swift outperforms BPF up to three times in terms of packet processing speed, and achieves much closer performance to the optimized C filters.
Detection of gene–gene interactions using multistage sparse and low‐rank regression

Finding an efficient and computationally feasible approach to deal with the curse of high‐dimensionality is a daunting challenge faced by modern biological science. The problem becomes even more severe when the interactions are the research focus. To improve the performance of statistical analyses, we propose a sparse and low‐rank (SLR) screening based on the combination of a low‐rank interaction model and the Lasso screening. SLR models the interaction effects using a low‐rank matrix to achieve parsimonious parametrization. The low‐rank model increases the efficiency of statistical inference and, hence, SLR screening is able to more accurately detect gene–gene interactions than conventional methods. Incorporation of SLR screening into the Screen‐and‐Clean approach (Wasserman and Roeder, 2009; Wu et al., 2010) is also discussed, which suffers less penalty from Boferroni correction, and is able to assign p‐values for the identified variables in high‐dimensional model. We apply the proposed screening procedure to the Warfarin dosage study and the CoLaus study. The results suggest that the new procedure can identify main and interaction effects that would have been omitted by conventional screening methods.
The Suppression of Instabilities via Biphase Interfaces During Bulk Fabrication of Nanograined Zr

Severe plastic deformation (SPD) is a common method to fabricate nano-grained metals. However for Zr, a structural metal for nuclear applications, obtaining a nanoscale grain structure via SPD has been problematic due to deformation twinning and phase transformations. Here, nanostructured hcp Zr is fabricated through a refinement process via the introduction of a biphase interface. Despite mechanical and thermal conditions known to chemically mix Zr and Nb, no intermixing is observed and the heterophase interfaces appear resistant to phase transformations and twinning. Increasing the density of chemically sharp Zr–Nb interfaces is a very different refinement mechanism than substructure development, stacking fault formation, or alloying.
The Conspicuous Absence of Placenta Consumption in Human Postpartum Females: The Fire Hypothesis

The absence of human placentophagy, the maternal consumption of the afterbirth, is puzzling given its ubiquity and probable adaptive value in other mammals. We propose that human fire use may have led to placentophagy avoidance in our species. In our environment of evolutionary adaptedness, gravid women would likely have been regularly exposed to smoke and ash, which is known to contain harmful substances. Because the placenta filters some toxicants which then accumulate there across pregnancy, maternal placentophagy may have had deleterious consequences for the overall fitness of mother, offspring, or both, leading to its elimination from our species' behavioral repertoire.
A new approach based on differential evolution algorithm for harmonic estimation problems

Electrical harmonic is an important issue affecting power quality of electrical systems. Estimation of power harmonics are essential to design filters to be utilized in electrical power systems for reducing harmonics and their effects on the electrical power systems. In this study, a harmonic estimator based on differential evolution algorithm is proposed for harmonic estimation problems shown in power systems. Analyses of designed estimator are performed for two different experiments. In addition, performances of proposed estimator are compared with available results of the literature. The achieved results of this study showed that the proposed harmonic estimator in this paper is superior among previously reported ones.