Miracle-dz/UniFAR-FTUs huggingface dataset:
NF-κB is essential for epithelial-mesenchymal transition and metastasis in a model of breast cancer progression

The transcription factor NF-κB is activated in a range of human cancers and is thought to promote tumorigenesis, mainly due to its ability to protect transformed cells from apoptosis. To investigate the role of NF-κB in epithelial plasticity and metastasis, we utilized a well-characterized in vitro/in vivo model of mammary carcinogenesis that depends on the collaboration of the Ha-Ras oncoprotein and TGF-β. We show here that the IKK-2/IκBα/NF-κB pathway is required for the induction and maintenance of epithelial-mesenchymal transition (EMT). Inhibition of NF-κB signaling prevented EMT in Ras-transformed epithelial cells, while activation of this pathway promoted the transition to a mesenchymal phenotype even in the absence of TGF-β. Furthermore, inhibition of NF-κB activity in mesenchymal cells caused a reversal of EMT, suggesting that NF-κB is essential for both the induction and maintenance of EMT. In line with the importance of EMT for invasion, blocking of NF-κB activity abrogated the metastatic potential of mammary epithelial cells in a mouse model system. Collectively, these data provide evidence of an essential role for NF-κB during distinct steps of breast cancer progression and suggest that the cooperation of Ras- and TGF-β–dependent signaling pathways in late-stage tumorigenesis depends critically on NF-κB activity.
Causal approximate inversion for control of structurally flexible manipulators using nonlinear inner-outer factorization

A control scheme for flexible-link manipulators is advanced which is based on the notion of nonlinear inner–outer factorization. It is well known that the inverse of the forward dynamics map from joint torques to manipulator tip motion is noncausal and cannot be implemented in conjunction with real-time path planning. The methods used here determine causal approximations for the inverse dynamics using the inverse of the outer (stable and minimum phase) factor and a static approximation for the inverse of the inner (lossless but nonminimum phase) factor. The Hamilton–Jacobi equation that arises is approximated by a state-dependent Riccati equation at each time step. The factorization procedure yields the corresponding joint trajectories which can serve as reference trajectories for closing joint-based feedback loops. Experimental results from a planar three-link manipulator with two flexible links demonstrate the efficacy of the procedure. © 2001 John Wiley & Sons, Inc.
Accretion Disks in Transient Systems

I review recent advances in our understanding of accretion disks in transient systems - the dwarf novae and the soft X-ray transients. The primary theme will be the ongoing development of theory in response to the observations. The accretion disk limit cycle model appears to provide a unifying framework within which we may begin to understand what is seen in different types of interacting binary stars, and also to constrain parameters which enter into the theory.
"Warm-up" along dimensions of movement in the ontogeny of exploration in rats and other infant mammals.

When some infant mammals are placed outside their nest, a sequence of exploratory behavior occurs, displaying a regular buildup and spread of activity. This "warm-up" involves repetition of movement along specific dimensions and an orderly transition from one dimension to the next, with cephalocaudal recruitment of body and limb segments. A similar principle of organization applies to neurological recovery from lateral hypothalamic akinesia.
QoS-aware Joint RRH activation and clustering in cloud-RANs

Cloud Radio Access Networks (Cloud-RAN) promise to leverage cloud computing capabilities to enhance the quality and coverage of wireless networks. A dense network of remote radio heads (RRHs) ensures less attenuation at the receiver side. However, two drawbacks are associated with such dense network: the first is the high energy consumption associated with such a large number of RRHs; the second is the interference experienced by the receiver due to close proximity of the transmitters. To address these challenges, we study the problem of joint activation and clustering of RRHs. Since the problem is NP-hard, we provide a two-step algorithm that can find an efficient solution. The first step uses linear-programming relaxation to find a feasible solution. The second step is a greedy approach to improve the utility function through gradual activation-clustering of RRHs. Our simulation results demonstrate the benefit in the joint design of activation and clustering over existing activation only approaches.
Formal Semantics and Reasoning about UML Class Diagram

The main way of coping with the complexity of software systems is to construct and use models expressed in UML. Unfortunately, the semantics (meaning) of models written in UML is not precisely defined. It may result in the incorrect interpretation of a model and make it hard to strictly verify a model and its transformation. In this paper we formally (mathematically) define UML class diagram and its semantics. The problem of consistency of the diagram is then introduced and some examples of inconsistencies are forwarded
A family of robot control strategies for intermittent dynamical environments

A formalism is developed for describing and analyzing a very simple representative class of robotic tasks that require dynamical dexterity-among them, the task of juggling. The authors review their empirical success to date with a new class of control algorithms for this task domain, called mirror algorithms. The formalism for representing the task domain and encoding within it the desired robot behavior enables them to prove that a suitable mirror algorithm is correct with respect to a specified task. <<ETX>>
Evaluation of Interfacial Frictional Properties for Fiber-Reinforced Ceramic Composites

An analytical model is developed to determine the frictional properties of the fiber-matrix interface in ceramic matrix composites using the indentation test. This model includes the effect of the interfacial friction stress arising from the transverse expansion of the fiber subjected to the compressive load. Two intrinsic interfacial properties, an interfacial friction limit (Tmass) and an interfacial coefficient of friction (μ), are determined for a SiC fiber-reinforced lithium aluminosilicate glass-ceramic matrix composite. It is found that during the indentation test, the interfacial friction coefficient is more pronounced at lower values of applied load. As the load increases, the behavior is dominated by the interfacial friction limit.
Political drivers of and barriers to Public-Private Partnerships: The role of political involvement

The application and design of public-private partnerships between the extremes of purely public or purely private task fulfilment in public services is, in practice, subject to political processes. Decisions about PPPs (realisation, arrangement) are taken in the political arena and are therefore not theoretical optimisation exercises. The interests and resources of the actors who participate in the political decision-making process as well as the rules of the political process have a powerful influence on whether, in what areas, and in what form PPPs are realised. The distance between this output and solutions that are theoretically desirable given certain ideal goals (e.g. efficiency) and conditions can be referred to as political bias. So what role does the political process play in the realisation of PPPs, in the actual design of PPPs, and in their performance? Using public choice and institutional economics theory this paper analyses what chances of success PPPs have given the existing decision-making structures and the inherent incentives for participating actors, and in what way political influence is brought to bear in the first place. Furthermore, aspects of political science in this field (legitimacy, democratic control) are considered as well. Using PPPs there might be a trade-off between reduced democratic control, but also reinforced market control. It turns out that political involvement might be both an important driver as well as an obstacle for (efficient) PPPs and that it is likely to decrease efficiency either way. A case study for userfinancing PPPs in the transport sector highlights the problems of political renitency.
Prediction of outcome in patients with acute respiratory distress syndrome by bronchoalveolar lavage inflammatory mediators

Acute respiratory distress syndrome (ARDS) is characterized by overwhelming lung inflammation. This study explored the inflammatory mediators in bronchoalveolar lavage fluid (BALF) for prognostic relevance in patients with infection-induced ARDS. Thirty-nine patients with infection-induced ARDS (28 pneumonia and 11 extrapulmonary sepsis) and two patients with cardiogenic lung edema as the control were included. The expression profiles of inflammatory mediators in BALF were compared between ARDS and cardiogenic lung edema. A group of inflammatory mediators that showed higher expression in ARDS was analyzed for their relationships with clinical features and outcome. We found that 17 patients who died had higher levels of interleukin (IL)-6 (P = 0.012), IL-8 (P = 0.001) and monocyte chemoattractant protein-1 (P = 0.036) in BALF compared with those who survived. Furthermore, there was an inverse relationship between the BALF levels of IL-6 (P = 0.026), IL-8 (P = 0.008) and macrophage inflammatory protein (MIP)-1α (P = 0.048) and the changes of lung compliance between days 1 and 4, whereas the BALF levels of IL-8 (P = 0.033) and MIP-1α (P = 0.029) were positively correlated with the changes of sequential organ failure assessment scores between days 1 and 4. In multivariate logistic regression analysis, only IL-8 (P = 0.013) and lung injury score (LIS) (P = 0.017) independently predicted the mortality, and IL-8 (P = 0.002) was most likely predictive of mortality in analysis of area under the receiver operating characteristic curve. In conclusion, we show the expression profiles of inflammatory mediators in BALF of infection-induced ARDS. Among the mediators, IL-8 is the most significant predictor for mortality, and several mediators are correlated with clinical severity. However, potential selection bias due to limited control subjects and lack of serum inflammatory mediator data suggest a necessity of further studies to confirm our findings.
Substantial Variation in Transplacental Transfer of Chemotherapeutic Agents in a Mouse Model

Objective: Data on the transplacental transfer of chemotherapeutic agents are lacking. We aimed to measure the maternofetal transfer of cytotoxic drugs in a mouse model. Study design: The transplacental transfer of doxorubicin (9 mg/kg), epirubicin (11 mg/kg), vinblastine (6 mg/kg), carboplatin (50 mg/kg), paclitaxel (10 mg/kg), and cytarabine (100 mg/kg) was tested in a C57/Bl6J mouse model. Ninety minutes after intravenous (IV) drug injection on gestational day 18.5, maternal and fetal blood were collected simultaneously. Plasma drug levels were determined using high performance liquid chromatography or atomic absorption spectrometry. Results: Fetal plasma concentrations of doxorubicin, epirubicin, vinblastine, and cytarabine were 5.1% ± 0.6% (n = 8), 4.8% ± 3.8% (n = 8), 13.8% ± 5.8% (n = 6), and 56.7% ± 22.6% (n = 6) of the maternal concentrations, respectively. Total platinum passed the mouse placenta easily (117.0% ± 38.9%, n = 6). Paclitaxel could not be detected in fetal plasma samples (n = 6). Conclusions: Substantial variations in transplacental transfer were noted among the tested drugs. Current findings contribute to the understanding of reported pregnancy outcomes in humans.
Second order analysis for joint source-channel coding with Markovian source

We derive the second order rates of joint source-channel coding, whose source obeys an irreducible and ergodic Markov process by introducing new distribution family, switched Gaussian convolution distribution, when the channel is a discrete memoryless. We also compare the joint source-channel scheme with the separation scheme in the second order regime.
Implied Volatility Surface Estimation Using Transductive Gaussian Fields Regression

Implied volatility estimation is one of the fundamental tasks for asset pricing and risk management. In this paper, we investigate the applicability of semi-supervised regression techniques to estimate an implied volatility surface from the real market option data. Specifically, we employ a transductive Gaussian field regression method since it is able to predict a distribution of the implied volatilities for unlabelled data using only partially labeled data. We've conducted simulation on S&P 500 index data before and after the global financial crisis with discussions of the observed empirical properties of the method.
New constraint in SHE-PWM for single phase inverter applications

This paper presents new constraints for Selective Harmonic Elimination (SHE)-PWM technique utilized in single phase applications. The proposed constraints eliminate all triplen harmonic orders naturally whereas they appear in all single-phase output voltage waveforms conventionally. The specified non-triplen harmonics are also eliminated through calculation of switching angles. Five-level high switching frequency voltage waveform has been opted in this paper to implement the introduced method; however, it can be applied on all multilevel voltage waveforms with even number of angles. The voltage THD analysis has been done to obtain optimum values for calculated switching angles while THD value is minimized. Moreover, the cancellation of triplen harmonics empowers single-phase inverters to deal with nonlinear loads beside linear ones. Some simulations are performed using a single phase 5-level modified packed U-cell (MPUC) inverter. Results are illustrated and discussed to prove the proper elimination of determined triplen and non-triplen harmonics orders by applying the proposed constraints in switching angles calculations.
Semi-supervised learning for text classification using feature affinity regularization

Most conventional semi-supervised learning methods attempt to directly include unlabeled data into training objectives. This paper presents an alternative approach that learns feature affinity information from unlabeled data, which is incorporated into the training objective as regularization of a maximum entropy model. The regularization favors models for which correlated features have similar weights. The method is evaluated in text classification, where feature affinity can be computed from feature co-occurrences in unlabeled data. Experimental results show that this method consistently outperforms baseline methods.
An Integrated Dialog Simulation Technique for Evaluating Spoken Dialog Systems

This paper proposes a novel integrated dialog simulation technique for evaluating spoken dialog systems. Many techniques for simulating users and errors have been proposed for use in improving and evaluating spoken dialog systems, but most of them are not easily applied to various dialog systems or domains because some are limited to specific domains or others require heuristic rules. In this paper, we propose a highly-portable technique for simulating user intention, utterance and Automatic Speech Recognition (ASR) channels. This technique can be used to rapidly build a dialog simulation system for evaluating spoken dialog systems. We propose a novel user intention modeling and generating method that uses a linear-chain conditional random field, a data-driven domain specific user utterance simulation method, and a novel ASR channel simulation method with adjustable error recognition rates. Experiments using these techniques were carried out to evaluate the performance and behavior of previously developed dialog systems designed for navigation dialogs, and it turned out that our approach is easy to set up and shows the similar tendencies of real users.
Managing Knowledge in Organizational Memory Using Topics Maps1

Organizational memories play a significant role in knowledge management, but several challenges confront their use. Artifacts of OM are many and varied. Access and use of the stored artifact are influenced by the userâ€™s understanding of these information objects as well as their context. Theories of distributed cognition and the notion of community of practice are used to develop a model of the knowledge management system. In the present work we look at a model for managing organizational memory knowledge. Topic maps are used in the model to represent user cognition of contextualized information. A visual approach to topic maps proposed in the model also allows for access and analysis of stored memory artifacts. The design and implementation of a prototype to test the feasibility of the model is briefly examined.
Effect of IT Investments on Customer Satisfaction Effect of Information Technology Investments on Customer Satisfaction : Theory and Evidence

This research addresses the following questions: Do information technology (IT) investments have an effect on customer satisfaction? What are the causal mechanisms that mediate the effect of IT systems on customer satisfaction? Does the effect of IT on customer satisfaction differ across industry sectors? Based on an analysis of longitudinal data on 50 U.S. firms for the period 1994-2000, we document the association between IT investments and customer satisfaction. We find support for the hypotheses that the effect of IT investments on customer satisfaction is mediated through the effect of IT on perceived quality and perceived value. Our results also indicate that the effect of IT investments on customer satisfaction differs between the manufacturing and service sectors. While prior work on the business value of IT at the firm level focused on financial and accounting measures, our research establishes the effect of IT investments on overall customer satisfaction of a firm. We propose and validate a theory of mediation effects of perceived quality and perceived value. This proposal has the potential to synthesize information systems effectiveness and marketing literature towards an integrative understanding of the relationship between IT investments and customer satisfaction.
Thermal Transfer Analysis of a Freezing Soil Medium with an Embedded Pipeline

This paper conducted the unsteady state heat transfer analyses, using the commercial code ABAQUS, for a freezing granite soil medium with an embedded pipeline in the closed system. The several physical values for granite soil of South Korea at various subzero temperatures were determined in laboratory tests. These studies were focused on the development of a computational scheme by applying the effective heat capacity model to the numerical procedures for predicting the temperature profiles along a buried pipeline and the frozen penetration depth. The proposed model took into consideration the phase-change effect of in situ pore water in the frozen fringe. A comparison of results obtained by the proposed model and the actual performances was valuable in establishing a level of confidence in the application of introduced theory.
Reconstructing transcription factor activities in hierarchical transcription network motifs

MOTIVATION A knowledge of the dynamics of transcription factors is fundamental to understand the transcriptional regulation mechanism. Nowadays, an experimental measure of transcription factor activities in vivo represents a challenge. Several methods have been developed to infer these activities from easily measurable quantities such as mRNA expression of target genes. A limitation of these methods is represented by the fact that they rely on very simple single-layer structures, typically consisting of one or more transcription factors regulating a number of target genes. RESULTS We present a novel statistical inference methodology to reverse engineer the dynamics of transcription factors in hierarchical network motifs such as feed-forward loops. The approach we present is based on a continuous time representation of the system where the high-level master transcription factor is represented as a two state Markov jump process driving a system of differential equations. We solve the inference problem using an efficient variational approach and demonstrate our method on simulated data and two real datasets. The results on real data show that the predictions of our approach can capture biological behaviours in a more effective way than single-layer models of transcription, and can lead to novel biological insights. AVAILABILITY http://homepages.inf. ed.ac. uk/gsanguin/software.html CONTACT g.sanguinetti@ed.ac. uk SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Enriching Mental Health Mobile Assessment and Intervention with Situation Awareness

Current mobile devices allow the execution of sophisticated applications with the capacity for identifying the user situation, which can be helpful in treatments of mental disorders. In this paper, we present SituMan, a solution that provides situation awareness to MoodBuster, an ecological momentary assessment and intervention mobile application used to request self-assessments from patients in depression treatments. SituMan has a fuzzy inference engine to identify patient situations using context data gathered from the sensors embedded in mobile devices. Situations are specified jointly by the patient and mental health professional, and they can represent the patient’s daily routine (e.g., “studying”, “at work”, “working out”). MoodBuster requests mental status self-assessments from patients at adequate moments using situation awareness. In addition, SituMan saves and displays patient situations in a summary, delivering them for consultation by mental health professionals. A first experimental evaluation was performed to assess the user satisfaction with the approaches to define and identify situations. This experiment showed that SituMan was well evaluated in both criteria. A second experiment was performed to assess the accuracy of the fuzzy engine to infer situations. Results from the second experiment showed that the fuzzy inference engine has a good accuracy to identify situations.
Endocrine Disruptors and Human Corpus Luteum: In vitro Effects of Phenols on Luteal Cells Function

Endocrine disruptors are well known to impair fertility. The aim of the present study was to investigate the effects of bisphenol A (BPA) and nonylphenol (p-NP) on human luteal function in vitro. In particular, in luteal cells isolated from 21 human corpora lutea progesterone, prostaglandin (PG) F2α, PGE2 and vascular endothelial growth factor (VEGF) release, as well as VEGF expression were evaluated. BPA and p-NP negatively affected both luteal steroidogenesis and luteotrophic/ luteolytic factors balance, without influencing VEGF mRNA expression. Actually, BPA and p-NP impaired human luteal cells function in vitro, underlining the already suggested correlation between phenols and reproductive failure.