Miracle-dz/UniFAR-FTUs huggingface dataset:
Corticosteroids differentially regulate secretion of IL-6, IL-8, and G-CSF by a human bronchial epithelial cell line.

Human airway epithelial cells play an active role in modulating airway inflammation by elaborating a variety of proinflammatory molecules, including cytokines. The purpose of this study was to define the role of corticosteroids in the regulation of cytokine gene transcription and secretion by human bronchial epithelial cells. In particular, we assessed whether dexamethasone was capable of inhibiting the tumor necrosis factor-alpha (TNF-alpha)-mediated secretion of interleukin-6 (IL-6), interleukin-8 (IL-8), and granulocyte colony-stimulating factor (G-CSF) by a human bronchial epithelial cell line (BEAS-2B). Stimulation with 20 ng/ml of TNF-alpha resulted in significant increases in secretion of immunoreactive IL-6, IL-8, and G-CSF that were maximal at 24 h. TNF-alpha-mediated IL-6, IL-8, and G-CSF secretion was concentration dependent and specific. In addition, stimulation with TNF-alpha resulted in significant increases in the quantity of IL-6, IL-8, and G-CSF mRNA as detected by reverse-transcription polymerase chain reaction. Dexamethasone preconditioning significantly inhibited both the secretion of immunoreactive IL-6 and the accumulation of IL-6 mRNA. Although dexamethasone appeared to reduce both the secretion of immunoreactive IL-8 and accumulation of IL-8 mRNA, the inhibitory effects did not reach statistical significance. Finally, dexamethasone did not inhibit either the secretion of immunoreactive G-CSF or the accumulation of G-CSF mRNA. In summary, our results suggest that corticosteroids have a differential effect on the regulation of cytokine secretion by human bronchial epithelial cells. (ABSTRACT TRUNCATED AT 250 WORDS)
An asymmetric robotic catapult based on the closed elastica for jumping robot

In this paper, we propose a new asymmetric robotic catapult based on the closed elastica. The conventional robotic catapults based on the closed elastica which the authors developed are the robotic elements for generating impulsive motions by utilizing a snap-through buckling. In a typical closed elastica, the two ends of an elastic strip are fixed to a passive rotational joint and an active rotational joint, respectively. Here we found that by adding only a range limitation to the passive rotational joint, compared to the conventional type, the deforming shape of the elastic strip becomes more complicated and 40% more elastic energy can be stored. Using this modification, we can develop a compact jumping robot which is able to leap over 700[mm] away and 200[mm] high.
Power Quality Indexes in an Agent-based Reconfiguration Strategy for Ship Power Systems

This paper presents an analysis of the introduction of power quality assessment through power quality indexes within the framework of an agent-based power system control. The objective is to account for power quality in the power management of systems where the total power of the loads significantly exceeds the power available from generation. This is typically the case of next generation all-electric warships.
Control-Informed Optimal Array Layout for Wave Farms

Somewhat similar to wind farms, commercial wave energy will be realized using farms of devices. However, for wave farms, both constructive and destructive interference may occur between individual devices; whereas, for wind farms, only destructive interference occurs. In order to maximize constructive interference, the layout of the wave farm must be optimized. In addition, power absorption may be improved by applying a control system technology to the farm of devices. As with many applications, there is a tendency in wave energy to separate the design of the array layout from the design of an energy maximizing control system. In this paper, we show that integrating the activities of optimal array layout design and control design are crucial if the full potential of the wave farm is to be realized. In particular, we show that a layout optimized without knowledge of the control system to be used can be inferior to the extent of recovering 40% less energy than a farm layout optimized with knowledge of the control system. This loss is significantly more than the difference in performance between a simple and a very complex control strategy.
2016 Ieee International Conference on Big Data (big Data) Coloc: Distributed Data and Container Colocation for Data-intensive Applications

—The performance of scalable analytic frameworks supporting data-intensive parallel applications often depends significantly on the time it takes to read input data. Therefore, existing frameworks like Spark and Flink try to achieve a high degree of data locality by scheduling tasks on nodes where the input data resides. However, the set of nodes running a job and its tasks is chosen by a cluster resource management system like YARN, which schedules containers without taking the location of data into account. Yet, the scheduling of the frameworks is restricted to the set of nodes the containers are running on. At the same time, many jobs in productive clusters are recurring with predictable characteristics. For these jobs, it is possible to plan in advance on which nodes to place a job's input data and execution containers. In this paper we present CoLoc, a lightweight data and container scheduling assistant for recurring data-intensive analytic jobs. CoLoc allows users to define related files that serve as input for the same job. It colocates related files on a set of nodes and offers this scheduling hint to the cluster manager to also place the jobs container on these nodes. The main advantage of CoLoc is a reduction of network transfers due to a higher data locality and locally performed operators like grouping or joining two or more datasets. We implement CoLoc on Hadoop YARN and HDFS, then evaluate it on a 40 node cluster using workloads based on Apache Flink and the TPC-H benchmark suite. Compared to YARN's default scheduler and HDFS's block placement scheduler, CoLoc reduces the execution time up to 35% for the tested data-intensive workloads.
Explorer Is the Homunculus " Aware " of Sensory Adaptation ?

General rights Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer content complies with UK legislation. If you believe that the public display of this file breaches copyright please contact openaccess@ed.ac. uk providing details, and we will remove access to the work immediately and investigate your claim. Neural activity and perception are both affected by sensory history. The work presented here explores the relationship between the physiological effects of adaptation and their perceptual consequences. Perception is modeled as arising from an encoder-decoder cascade, in which the en-coder is defined by the probabilistic response of a population of neurons, and the decoder transforms this population activity into a perceptual estimate. Adaptation is assumed to produce changes in the encoder, and we examine the conditions under which the decoder behavior is consistent with observed perceptual effects in terms of both bias and dis-criminability. We show that for all decoders, discriminability is bounded from below by the inverse Fisher information. Estimation bias, on the other hand, can arise for a variety of different reasons and can range from zero to substantial. We specifically examine biases that arise when the decoder is fixed, " unaware " of the changes in the encoding population (as opposed to " aware " of the adaptation and changing accordingly). We simulate the effects of adaptation on two well-studied sensory attributes, motion direction and contrast, assuming a gain change description of en-coder adaptation. Although we cannot uniquely constrain the source of decoder bias, we find for both motion and contrast that an " unaware " de-coder that maximizes the likelihood of the percept given by the preadap-tation encoder leads to predictions that are consistent with behavioral data. This model implies that adaptation-induced biases arise as a result of temporary suboptimality of the decoder.
Adaptive beamforming using complex-valued Radial Basis Function neural networks

Beamforming is an array signal processing problem of forming a beam pattern of an array of sensors. In doing so, beams are directed to the desired direction (beam-pointing) and the nulls are directed to interference direction (null-steering). In this paper, the performance of beamforming using the Fully Complex-valued RBF network (FC-RBF) with the fully complex-valued activation function is compared with the performance of the existing complex-valued RBF neural networks. It was observed that the FC-RBF network performed better than the other complex-valued RBF networks in suppressing the nulls and steering beams, as desired. The learning speed of the FC-RBF network was also faster than the Complex-valued Radial Basis Function network. Comparison of these performances with the optimum Matrix method showed that the beampattern of the FC-RBF beamformer was closer to the beampattern of the matrix method.
Measurement and analysis of online gaming services on mobile WiMAX networks

Online games have been played mainly in desktop computers over wired networks because of high speed and intensive computation requirements. The advances in mobile devices and ever increasing wireless link bandwidth motivate us to study whether players can enjoy online gaming over broadband wireless networks such as mobile Worldwide Inter-operability for Microwave Access WiMAX. In this paper, we carry out comprehensive measurements of the World of Warcraft WoW over the mobile WiMAX in Seoul, Korea, and analyze the network performance focusing on two aspects: 1 network layer dynamics such as round trip time, jitter, and packet loss and 2 WiMAX link layer statistics such as the radio signal strength, handovers, and piggyback mechanism. From the empirical data, we set up performance models and evaluate the performance of WoW over WiMAX. We also discuss how to improve the service quality of online gaming over WiMAX.Copyright © 2013 John Wiley & Sons, Ltd.
Power converter line synchronization using a discrete Fourier transform (DFT) based on a variable sample rate

Line synchronization of grid connected power converters is a well recognized problem when the grid is weak, or derives from a remote area power supply with poor frequency regulation. Such systems can suffer significant line voltage distortion due to notches caused by power device switching and/or low frequency harmonic content, which can easily corrupt the output of a conventional zero crossing detector. This paper presents a method of filtering the incoming grid voltage using a recursive discrete Fourier transform (DFT). The filter provides a high degree of noise immunity but does produce a phase shift between the incoming grid voltage and the filtered output voltage when the DFT time window does not match the grid period. Two methods of compensating this phase shift are presented, based on tracking the drift in the phase predicted by the recursive DFT. The first method makes a deadbeat adjustment to the time window (thereby changing the sampling rate) while the second approach calculates the phase error based on the linear phase response of the DFT. These compensation algorithms can correct for discrepancies of at least 25% between the DFT time window and the system period, and can track grid frequencies with slew rates as high as 40 Hz/s with negligible phase shift (<2/spl deg/) between the grid voltage input and the filtered output waveforms.
Hilbert Space Embeddings of Predictive State Representations

Predictive State Representations (PSRs) are an expressive class of models for controlled stochastic processes. PSRs represent state as a set of predictions of future observable events. Because PSRs are defined entirely in terms of observable data, statistically consistent estimates of PSR parameters can be learned efficiently by manipulating moments of observed training data. Most learning algorithms for PSRs have assumed that actions and observations are finite with low cardinality. In this paper, we generalize PSRs to infinite sets of observations and actions, using the recent concept of Hilbert space embed-dings of distributions. The essence is to represent the state as one or more nonparametric conditional embedding operators in a Reproducing Kernel Hilbert Space (RKHS) and leverage recent work in kernel methods to estimate, predict, and update the representation. We show that these Hilbert space embeddings of PSRs are able to gracefully handle continuous actions and observations, and that our learned models outperform competing system identification algorithms on several prediction benchmarks.
Tactile Sensing for Mobile Manipulation

Tactile information is valuable in determining properties of objects that are inaccessible from visual perception. In this paper, we present a tactile perception strategy that allows a mobile robot with tactile sensors in its gripper to measure a generic set of tactile features while manipulating an object. We propose a switching velocity-force controller that grasps an object safely and reveals, at the same time, its deformation properties. By gently rolling the object, the robot can extract additional information about the contents of the object. As an application, we show that a robot can use these features to distinguish the internal state of bottles and cans-purely from tactile sensing-from a small training set. The robot can distinguish open from closed bottles and cans and full ones from empty ones. We also show how the high-frequency component in tactile information can be used to detect movement inside a container, e.g., in order to detect the presence of liquid. To prove that this is a hard recognition problem, we also conducted a comparative study with 17 human test subjects. The recognition rates of the human subjects were comparable with that of the robot.
A Topology-Preserving Growing Neural Network for Real-Time Representation of Objects and Their Motion

Self-organizing neural networks endeavour to preserve the topology of an input space by means of competitive learning. This capability is used for obtaining reduced representation of objects that can be used in classification or recognition tasks. The model is extended to be also employed in tracking and motion analysis. Moreover, these applications usually have real-time constraints imposed on them. We propose the Growing Neural Gas (GNG) model due to its iterative and incremental learning process that allows. According to the available time to perform the representation, parameters of the GNG are chosen in order to finish the adaptation before the deadline. However, the quality of the representation can be affected by this parameterization, reason why we have studied topology preservation of several variants of the GNG. As self-organizing neural networks allow the learning of new patterns without beginning again the adaptation process, tracking and motion analysis is obtained by studying the dynamics of the network throughout time. We have also designed a parallel hardware architecture for our representation method, evaluating its temporal costs and processing rates by a simulation over a FPGA.
Constitutive Androgen Receptor-Null Mice Are Sensitive to the Toxic Effects of Parathion: Association with Reduced Cytochrome P450-Mediated Parathion Metabolism

Constitutive androgen receptor (CAR) is activated by several chemicals and in turn regulates multiple detoxification genes. Our research demonstrates that parathion is one of the most potent, environmentally relevant CAR activators with an EC50 of 1.43 μM. Therefore, animal studies were conducted to determine whether CAR was activated by parathion in vivo. Surprisingly, CAR-null mice, but not wild-type (WT) mice, showed significant parathion-induced toxicity. However, parathion did not induce Cyp2b expression, suggesting that parathion is not a CAR activator in vivo, presumably because of its short half-life. CAR expression is also associated with the expression of several drug-metabolizing cytochromes P450 (P450). CAR-null mice demonstrate lower expression of Cyp2b9, Cyp2b10, Cyp2c29, and Cyp3a11 primarily, but not exclusively in males. Therefore, we incubated microsomes from untreated WT and CAR-null mice with parathion in the presence of esterase inhibitors to determine whether CAR-null mice show perturbed P450-mediated parathion metabolism compared with that in WT mice. The metabolism of parathion to paraoxon and p-nitrophenol (PNP) was reduced in CAR-null mice with male CAR-null mice showing reduced production of both paraoxon and PNP, and female CAR-null mice showing reduced production of only PNP. Overall, the data indicate that CAR-null mice metabolize parathion slower than WT mice. These results provide a potential mechanism for increased sensitivity of individuals with lower CAR activity such as newborns to parathion and potentially other chemicals due to decreased metabolic capacity.
Chemotherapy treatment in pediatric patients with acute myeloid leukemia receiving antimicrobial prophylaxis leads to a relative increase of colonization with potentially pathogenic bacteria in the gut.

BACKGROUND Normally, humans are protected against infections by their anaerobic intestinal microorganisms providing colonization resistance. In immunocompromised patients, the endogenous intestinal gram-positive and gram-negative pathogens often cause infectious complications. Therefore, we analyzed the effect of chemotherapy treatment and antimicrobial prophylaxis on intestinal bacterial populations (microbiota) among pediatric patients with acute myeloid leukemia who are prone to intestinal mucositis and infections. METHODS During 36 chemotherapy cycles, fecal samples were collected from pediatric patients with acute myeloid leukemia. Fecal bacterial populations were analyzed by polymerase chain reaction denaturing gradient gel electrophoresis fingerprinting. Fluorescent in situ hybridization analysis with specific bacterial oligonucleotide probes was used to quantify the fecal bacteria. RESULTS During chemotherapy treatment, the total number of bacteria in fecal samples was 10(9) per gram of dry weight feces, which was 100-fold lower than than in healthy control samples. Fluorescent in situ hybridization analysis showed that this decrease was the result of an up to 10,000-fold decrease in anaerobic bacteria, partly compensated for by a 100-fold increase in potentially pathogenic enterococci. Additional experiments showed that both prophylactic and therapeutic use of antibiotics could not sufficiently explain the tremendous changes in intestinal microbial composition. In vitro tests showed a direct bacteriostatic effect of chemotherapeutics. CONCLUSIONS Patients with acute myeloid leukemia treated with chemotherapy and prophylactic antibiotics are unable to maintain colonization resistance because of a decrease in anaerobic bacteria and an increase in potentially pathogenic aerobic enterococci. We hypothesize that this disturbance in the balance between anaerobic and aerobic bacteria will further increase the risk of gram-positive aerobic infections among immunocompromised patients with cancer.
An assessment of nonconvulsive seizures in the intensive care unit using continuous EEG monitoring

Of 49 patients with nonconvulsive seizures studied with continuous EEG monitoring, the overall mortality was 33% (16/49). Of the 23 patients with nonconvulsive status epilepticus (NCSE), 13 died (mortality 57%). Individual variables significantly associated with mortality were age, presence of NCSE, seizure duration, hospital and NICU length of stay, and delay to diagnosis and etiology (acute illness versus remote symptomatic). With multivariate logistic regression, only seizure duration (p = 0.0057, OR = 1.131/hour) and delay to diagnosis (p = 0.0351, OR = 1.039/hour) were associated with increased mortality. Acute symptomatic cases could not be adequately classified as either absence, simple, or complex partial status epilepticus when the impairment of consciousness arose from the initial illness. Current classifications of status epilepticus are inadequate for such cases. NEUROLOGY 1996;47: 83-89
Optimized Asymptotic Puncturing Distributions for Different LDPC Code Constructions

In this paper, we describe a method, how to optimize the asymptotic puncturing distributions for low-density parity-check codes constructed with different algorithms. Therefore, we generalize the discretized density evolution such that we can take care of the structure of the code. We show by density evolution and by simulations that even for the same degree distributions the optimized asymptotic puncturing distributions vary considerably for different construction algorithms. Furthermore, we demonstrate the performance gain by using the designed puncturing distributions compared to known puncturing distributions
Sketching concurrent data structures

We describe PSketch, a program synthesizer that helps programmers implement concurrent data structures. The system is based on the concept of sketching, a form of synthesis that allows programmers to express their insight about an implementation as a partial program: a sketch. The synthesizer automatically completes the sketch to produce an implementation that matches a given correctness criteria. PSketch is based on a new counterexample-guided inductive synthesis algorithm (CEGIS) that generalizes the original sketch synthesis algorithm from Solar-Lezama et.al. to cope efficiently with concurrent programs. The new algorithm produces a correct implementation by iteratively generating candidate implementations, running them through a verifier, and if they fail, learning from the counterexample traces to produce a better candidate; converging to a solution in a handful of iterations. PSketch also extends Sketch with higher-level sketching constructs that allow the programmer to express her insight as a "soup" of ingredients from which complicated code fragments must be assembled. Such sketches can be viewed as syntactic descriptions of huge spaces of candidate programs (over 108 candidates for some sketches we resolved). We have used the PSketch system to implement several classes of concurrent data structures, including lock-free queues and concurrent sets with fine-grained locking. We have also sketched some other concurrent objects including a sense-reversing barrier and a protocol for the dining philosophers problem; all these sketches resolved in under an hour.
Does a diffuse growth pattern predict for survival in patients with low-grade follicular lymphoma?

Low-grade follicular lymphoma (LGFL) is known to have a good prognosis. However, the clinical relevance of the presence and extent of diffuse growth areas within LGFL is not clear. Therefore, we studied 457 patients with nodal LGFL seen over a 20-year period (1982–2002). Relevant clinical and survival data were obtained and the pathology specimens were subclassified into predominantly follicular LGFL (≥80% follicular areas), significantly follicular LGFL (30–70% follicular areas), significantly diffuse LGFL (<30% follicular areas) and pure diffuse follicle centre lymphoma (DFCL). The majority of the patients were treated with anthracycline-based regimens. Patients with DFCL were slightly older (median age, 67 years), more likely to have bulky disease (>5 cm), and often had suboptimal biopsies. However, no association was observed between the extent of diffuse areas and survival across the four subgroups. We conclude that the subclassification of LGFL based on the extent of diffuse areas does not have clinical relevance.