Miracle-dz/UniFAR-FTUs huggingface dataset:
Cyclooxygenases: structural and functional insights Research on COX structure and function in the authors' laboratory is supported by grants from the National Institutes of Health (CA-89450 and GM-15431). Published, JLR Papers in Press, October 23, 2008.

Cyclooxygenase (COX; prostaglandin G/H synthase, EC 1.14.99.1) catalyzes the first two steps in the biosynthesis of prostaglandins (PGs). The two COX isoforms COX-1 and COX-2 are the targets of the widely used nonsteroidal anti-inflammatory drugs, indicating a role for these enzymes in pain, fever, inflammation, and tumorigenesis. The ubiquitous constitutive expression of COX-1 and inducible expression of COX-2 have led to the widely held belief that COX-1 produces homeostatic PGs, while PGs produced by COX-2 are primarily pathophysiological. However, recent discoveries call this paradigm into question and reveal as yet underappreciated functions for both enzymes. This review focuses on some of these new insights.
Addressing Big Data Time Series: Mining Trillions of Time Series Subsequences Under Dynamic Time Warping

Most time series data mining algorithms use similarity search as a core subroutine, and thus the time taken for similarity search is the bottleneck for virtually all time series data mining algorithms, including classification, clustering, motif discovery, anomaly detection, and so on. The difficulty of scaling a search to large datasets explains to a great extent why most academic work on time series data mining has plateaued at considering a few millions of time series objects, while much of industry and science sits on billions of time series objects waiting to be explored. In this work we show that by using a combination of four novel ideas we can search and mine massive time series for the first time. We demonstrate the following unintuitive fact: in large datasets we can exactly search under Dynamic Time Warping (DTW) much more quickly than the current state-of-the-art Euclidean distance search algorithms. We demonstrate our work on the largest set of time series experiments ever attempted. In particular, the largest dataset we consider is larger than the combined size of all of the time series datasets considered in all data mining papers ever published. We explain how our ideas allow us to solve higher-level time series data mining problems such as motif discovery and clustering at scales that would otherwise be untenable. Moreover, we show how our ideas allow us to efficiently support the uniform scaling distance measure, a measure whose utility seems to be underappreciated, but which we demonstrate here. In addition to mining massive datasets with up to one trillion datapoints, we will show that our ideas also have implications for real-time monitoring of data streams, allowing us to handle much faster arrival rates and/or use cheaper and lower powered devices than are currently possible.
Dimensioning of painful procedures and interventions for acute pain relief in premature infants 1

ABSTRACT Objective: to dimension the exposure of premature infants to painful procedures, relating the distribution of the exposure to contextual factors, as well as to describe the pharmacological and non-pharmacological interventions health professionals use during the first two weeks of the infant’s hospitalization at two neonatal services. Method: descriptive-exploratory study in which the professionals registered the painful procedures and pain relief interventions on a specific form in the patient file. Results: the daily average of the 89 premature infants was 5.37 painful procedures, corresponding to 6.56 during the first week of hospitalization and 4.18 during the second week (p<0.0001). The most frequent procedures were nasal/oral (35.85%) and tracheal aspirations (17.17%). The children under invasive ventilation were the most exposed to painful procedures (71.2%). Only 44.9% of the painful procedures received some intervention for the purpose of pain relief, the most frequent being sucrose (78.21%) and continuing sedation (19.82%). Conclusion: acute pain was undertreated at these neonatal services, recommending greater sensitization of the team for the effective use of the existing protocol and implementation of other knowledge transfer strategies to improve neonatal pain management.
The Impact of Distributed Generation on Power Transmission Grid Dynamics

In this paper we investigate the impact of the introduction of distributed generation on the robustness of the power transmission grid using a dynamic model of the power transmission system (OPA). It is found that with different fractions and distributions of distributed generation, varied dynamics are possible. An important parameter is found to be the ratio of the variability of the distributed generation to the generation capacity margin. Somewhat counter-intuitively, in some of these cases the robustness of the transmission grid can be degraded with the potential for an increased risk of large failures with increased distributed generation if not done carefully.
Probable Phase Composition of the Mineral in Bone

Abstract Formulas proposed for the mineral of bone were reviewed. Literature data were collected where Ca, P, Na, Mg and CO3 are determined in the same samples. These data were analyzed for their conformity to the above mentioned formulas. According to this analysis Mg is contained in a phase having the Ca/P of magnesium whitlockite within the limits of error. Na is contained in a carbonated calcium phosphate phase which in analogy with synthetic systems must have the apatite structure. The Ca/P ratio of the remaining "rest phase" is 2. This is based on the composi tion of 101 bone mineral samples taken from fishes, reptiles, amphibians, birds and mammals. The CO3 content of the bone samples agrees with the formula Ca8 (PO4)4 (CO3) (OH)2 · x H2O for the "rest phase" within the limits of experimental error. Such a compound has, however, not been found in synthetic systems. Human bone contains about 15% magnesium whitlockite, 25% of the Na and CO3 containing apatite and the rest is the carbonated calcium phosphate with Ca/P = 2. It is presumed that this compound has a structure similar to that of octo calcium phosphate and that most of the citrate ions which always occur in bone mineral samples are in corporated in that phase.
Morphological changes of poly(DI‐lactide‐co‐glycolide) nano‐particles containing ascorbic acid during in vitro degradation process

Poly(dl‐lactide‐co‐glycolide) powder composed of uniform particles with the mean particle size in the range of 110–170 nm was obtained from commercial granules. Ascorbic acid in different concentrations was encapsulated into the poly(dl‐lactide‐co‐glycolide) particles. Degradation of the latter in terms of morphological changes in the physiological solution was followed. Within a period of 2 months, the particles completely degrade and all the ascorbic acid is released. The samples were characterized by ultraviolet spectroscopy and scanning electron microscopy.
On the Importance of Comprehensible Classification Models for Protein Function Prediction

The literature on protein function prediction is currently dominated by works aimed at maximizing predictive accuracy, ignoring the important issues of validation and interpretation of discovered knowledge, which can lead to new insights and hypotheses that are biologically meaningful and advance the understanding of protein functions by biologists. The overall goal of this paper is to critically evaluate this approach, offering a refreshing new perspective on this issue, focusing not only on predictive accuracy but also on the comprehensibility of the induced protein function prediction models. More specifically, this paper aims to offer two main contributions to the area of protein function prediction. First, it presents the case for discovering comprehensible protein function prediction models from data, discussing in detail the advantages of such models, namely, increasing the confidence of the biologist in the system's predictions, leading to new insights about the data and the formulation of new biological hypotheses, and detecting errors in the data. Second, it presents a critical review of the pros and cons of several different knowledge representations that can be used in order to support the discovery of comprehensible protein function prediction models.
Learning Qualitative Models for Systems with Multiple Operating Regions

The problem of learning qualitative models of physical systems from observations of its behaviour has been addressed by several researchers in recent years. Most current techniques limit themselves to learning a single qualitative di erential equation to model the entire system. However, many systems have several qualitative differential equations underlying them. In this paper, we present an approach to learning the models for such systems. Our technique divides the behaviours into segments, each of which can be explained by a single qualitative di erential equation. The qualitative model for each segment can be generated using any of the existing techniques for learning a single model. We show the results of applying our technique to several examples and demonstrate that it is e ective.
Effects of dietary saturated and unsaturated fatty acids on fecal bile acids and colon carcinogenesis induced by azoxymethane in rats.

To determine whether the kind of dietary fat affects colon carcinogenesis, male Donryu rats were fed a 5% fat diet containing linoleate, an unsaturated fat, or stearate, a saturated fat, in semipurified fat-free chow. The rats were given azoxymethane (7.4 mg/kg body weight) s.c. once a week for 11 weeks and killed 15 weeks after the last injection of the carcinogen. The rats on the unsaturated fat diet had a significantly higher incidence of colon tumors. Fatty acid analysis of cholesterol esters in the liver and examination of the amount of fecal bile acids showed that the unsaturated fat diet increased the level of cholesterol linoleate and arachidonate in the liver and also increased the fecal excretion of bile acids, especially that of lithocholic acid. The colon tumors in rats on the unsaturated fat diet, compared with those in rats on the saturated fat diet, contained a higher level of lysophosphatidylcholine. These results suggest that increased fecal excretion of bile acids due to increased polyunsaturated cholesterol esters in the liver stimulates phospholipase A2 activity of colon initiated cells and enhances colon carcinogenesis in rats on the unsaturated fat diet.
Quantification of the DNA Cleavage and Packaging Proteins UL15 and UL28 in A and B Capsids of Herpes Simplex Virus Type 1

ABSTRACT The proteins produced by the herpes simplex virus type 1 (HSV-1) genes UL15 and UL28 are believed to form part of the terminase enzyme, a protein complex essential for the cleavage of newly synthesized, concatameric herpesvirus DNA and the packaging of the resultant genome lengths into preformed capsids. This work describes the purification of recombinant forms of pUL15 and pUL28, which allowed the calculation of the average number of copies of each protein in A and B capsids and in capsids lacking the putative portal encoded by UL6. On average, 1.0 (±0.29 [standard deviation]) copies of pUL15 and 2.4 (±0.97) copies of pUL28 were present in B capsids, 1.2 (±0.72) copies of pUL15 and 1.5 (±0.86) copies of pUL28 were found in mutant capsids lacking the putative portal protein pUL6, and approximately 12.0 (±5.63) copies of pUL15 and 0.6 (±0.32) copies of pUL28 were present in each A capsid. These results suggest that the packaging machine is partly comprised of approximately 12 copies of pUL15, as found in A capsids, with wild-type B and mutant UL6(−) capsids containing an incomplete complement of cleavage and packaging proteins. These results are consistent with observations that B capsids form by default in the absence of packaging machinery in vitro and in vivo. In contrast, A capsids may be the result of initiated but aborted attempts at DNA packaging, resulting in the retention of at least part of the DNA packaging machinery.
Closed-loop multiple view registration

In this study, a novel algorithm is presented for multiple view registration with a loop constraint. Instead of estimating the global pose of each view, the proposed algorithm is designed via the analysis of relative poses. Our method proves that the rotation and translation components can be exactly decoupled and further derivation reveals the mechanism of how the influence of a single update of rotation on one view of the loop will be propagated into the whole loop, resulting in an efficient, accurate and robust performance even for complicated cases such as 1000 views in a loop. Meanwhile, Lagrange multiplier is utilized so that the loop constraint is satisfied and the matrix exponentiated gradient method is used to optimize the solution. Our method is implemented in an iterative way, where the rotation matrices are updated on manifold so that their orthonormality can be well preserved in each iteration. The algorithm is verified by a series of tests and experimental results demonstrate the effectiveness and convergence of our algorithm.
Globally Optimal Training of Generalized Polynomial Neural Networks with Nonlinear Spectral Methods

The optimization problem behind neural networks is highly non-convex. Training with stochastic gradient descent and variants requires careful parameter tuning and provides no guarantee to achieve the global optimum. In contrast we show under quite weak assumptions on the data that a particular class of feedforward neural networks can be trained globally optimal with a linear convergence rate with our nonlinear spectral method. Up to our knowledge this is the first practically feasible method which achieves such a guarantee. While the method can in principle be applied to deep networks, we restrict ourselves for simplicity in this paper to one and two hidden layer networks. Our experiments confirm that these models are rich enough to achieve good performance on a series of real-world datasets.
Analysis of mutual duration and noise effects in speaker recognition: benefits of condition-matched cohort selection in score normalization

The biometric and forensic performance of automatic speaker recognition systems degrades under noisy and short probe utter-ance conditions. Score normalization is an effective tool taking into account the mismatch of reference and probe utterances. In an adaptive symmetric score normalization scheme for state-of-the-art i-vector recognition systems, a set of cohort speakers are employed to calculate the mean and variance of impostor scores when compared to reference and probe i-vectors. In dealing with real-life conditions where the quality of audio recordings in test phase does not match enrolment utterance(s) of speakers, we demonstrate the effectiveness of utilizing a condition-matched cohort set for score normalization. The cohort set audio material is shortened and degraded by noise in different reasonable and controlled signal-to-noise ratios according to expected test conditions, yielding in multiple set of cohorts. Further, we propose automatic cohort pre-selection based on modeling each degradation category. For each i-vector, a quality vector is assigned as the posterior probability of degradation classes. The cohort set is then formed by i-vectors representing small KL-divergence of respective quality vectors when compared to reference and probe. Further gains are observed by including this quality vector also into the score calibration.
Homocysteine Toxicity in Escherichia coli Is Caused by a Perturbation of Branched-Chain Amino Acid Biosynthesis

ABSTRACT In Escherichia coli the sulfur-containing amino acid homocysteine (Hcy) is the last intermediate on the methionine biosynthetic pathway. Supplementation of a glucose-based minimal medium with Hcy at concentrations greater than 0.2 mM causes the growth of E. coli Frag1 to be inhibited. Supplementation of Hcy-treated cultures with combinations of branched-chain amino acids containing isoleucine or with isoleucine alone reversed the inhibitory effects of Hcy on growth. The last intermediate of the isoleucine biosynthetic pathway, α-keto-β-methylvalerate, could also alleviate the growth inhibition caused by Hcy. Analysis of amino acid pools in Hcy-treated cells revealed that alanine, valine, and glutamate levels are depleted. Isoleucine could reverse the effects of Hcy on the cytoplasmic pools of valine and alanine. Supplementation of the culture medium with alanine gave partial relief from the inhibitory effects of Hcy. Enzyme assays revealed that the first step of the isoleucine biosynthetic pathway, catalyzed by threonine deaminase, was sensitive to inhibition by Hcy. The gene encoding threonine deaminase, ilvA, was found to be transcribed at higher levels in the presence of Hcy. Overexpression of the ilvA gene from a plasmid could overcome Hcy-mediated growth inhibition. Together, these data indicate that in E. coli Hcy toxicity is caused by a perturbation of branched-chain amino acid biosynthesis that is caused, at least in part, by the inhibition of threonine deaminase.
A Fault Tolerant Data Structure for Peer-to-Peer Range Query Processing

We present a fault tolerant dynamic data structure based on a constant-degree Distributed Hash Table (DHT) called FissionE that supports orthogonal range search in d-dimensional space. A publication algorithm, which distributes data objects among all nodes in the network is described, along with a search algorithm that processes range queries and reports all objects in range to the query issuer. Routing messages between two nodes is performed by the FissionE routing algorithm. The worst case orthogonal range search cost in our data structure with n nodes is O(log n+m) messages plus reporting cost, where m is the minimum number of nodes intersecting the query. Storing d complete copies of each data object on d different nodes provides redundancy for our scheme. This redundancy permits completely answering a query in the case of simultaneous failure of d− 1 nodes.
Digital Witness: Safeguarding Digital Evidence by Using Secure Architectures in Personal Devices

Personal devices contain electronic evidence associated with the behavior of their owners and other devices in their environment, which can help clarify the facts of a cyber-crime scene. These devices are usually analyzed as containers of proof. However, it is possible to harness the boom of personal devices to define the concept of digital witnesses, where personal devices are able to actively acquire, store, and transmit digital evidence to an authorized entity reliably and securely. This article introduces this novel concept, providing a preliminary analysis on the management of digital evidence and the technologies that can be used to implement it with security guarantees in IoT environments. Moreover, the basic building blocks of a digital witness are defined.
A Mathematician Looks at Answer Set Programming

We shall discuss a variety of results on Answer Set Programming based on the work of author with Marek, Nerode, Blair and Cenzer that have arisen by looking at Answer Set Programming from a mathematical perspective. This includes work with Nerode and Marek (Marek, Nerode, & Remmel 1990; 1992c; 1992b; 1992a; 1994; 1997; 1999) Nonmonotonic Proof Systems which allows one to gives a common generalization of many nonmonotonic formalisms and provide a basis for giving uniform proofs of a number of complexity results, work with Marek and Cenzer (Marek & Remmel 2004b; Cenzer, Marek, & Remmel 2004; 2005; Pollet & Remmel 1997) on Answer Set Programming with Set Constraints, and recent work with Blair and Marek (Blair, Marek, & Remmel 2001; 2004) on Set Based Logic Programming with the addition of monotonic idempotent operators. If time allows, we will also talk about some recent work with Marek (Marek & Remmel 2001; 2002; 2004b; 2004a; 2007)
Methylation‐Specific PCR

DNA methylation is a dynamic covalent modification of DNA that is found in transcriptionally repressed regions of the genome. In concert with other epigenetic modifications, such as the repressive histone H3 modifications of lysine 9 and lysine 27 methylation, DNA methylation acts to repress gene expression through the formation of condensed chromatin structures. Thus, DNA methylation is a marker for gene repression. Methylation‐specific PCR (MSP) is a rapid and inexpensive method that can be used to determine the methylation status of DNA. MSP can be used to assess CpG methylation at imprinted genes and on the inactive X chromosome. In addition, MSP can be used to investigate the aberrant DNA methylation that occurs in diseases such as fragile X syndrome and in many types of cancers. MSP is rapid, inexpensive, and relatively simple to perform and provides a powerful tool to investigate these epigenetic processes. Curr. Protoc. Hum. Genet. 61:10.6. 1‐10.6. 14. © 2009 by John Wiley & Sons, Inc.
A N ovel Current-Mode Very L ow Power Analog CM O S F our Quadrant Multiplier

In this paper, a novel current mode CMOS four-quadrant analog multiplier circuit is presented. The multiplication is implemented by four translinear loops with MOS transistors operating in weak inversion. Information carrying signals are differential balanced currents. The multiplier circuit has been implemented in a test chip in a standard 0.35 m CMOS technology. The experimental measurements (dc bias current of 250 nA and a power supply of 2.0 V) show a bandwidth of 200 kHz and a THD figure value lower than 0.9 %. The multiplier features a wide signal dynamic range and linearity, low power consumption (the maximum power consumption is of 5.5·10 W) and very low area (18.7 10 mm). The multiplier is suitable for a wide range of analog signal processing applications. Due to the low power and silicon area consumption, scalability and modularity can be also easily integrated in massive parallel systems.
Scaling perception towards autonomous object manipulation — in knowledge lies the power

Mobile robots operating in a human environment face the challenge of recognizing objects that possess a multitude of different visual characteristics, affordances, and are found in visually challenging scenes. Because of this, perceptual capabilities of such robots need to go beyond detection or categorization of objects, and be able to answer queries not only about where certain objects are located based on their class label, but also about functional properties of these. To achieve an optimal performance, robots need to be aware of their environment, the task that they are to execute, and their perceptual capabilities. Given this knowledge, robotic agents need adequate mechanisms that apply the right method at the right time, in the right situation. In this paper we present a self-adaptive robotic perception system, that acts as a planner for task aware robot manipulation and enables querying on a broad domain. This is done through extending our existing perception framework, ROBOSHERLOCK, with the capability to adapt its perception pipelines based on the query, using knowledge-based reasoning. We will demonstrate the success of the approach, by presenting challenging queries, where the benefits of integrating knowledge processing into perception systems is shown.