Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantitation of signal transduction

Conventional qualitative approaches to signal transduction provide powerful ways to explore the architecture and function of signaling pathways. However, at the level of the complete system, they do not fully depict the interactions between signaling and metabolic pathways and fail to give a manageable overview of the complexity that is often a feature of cellular signal transduction. Here, we introduce a quantitative experimental approach to signal transduction that helps to overcome these difficulties. We present a quantitative analysis of signal transduction during early mitogen stimulation of lymphocytes, with steady‐state respiration rate as a convenient marker of metabolic stimulation. First, by inhibiting various key signaling pathways, we measure their relative importance in regulating respiration. About 80% of the input signal is conveyed via identifiable routes: 50% through pathways sensitive to inhibitors of protein kinase C and MAP kinase and 30% through pathways sensitive to an inhibitor of calcineurin. Second, we quantify how each of these pathways differentially stimulates functional units of reactions that produce and consume a key intermediate in respiration: the mitochondrial membrane potential. Both the PKC and calcineurin routes stimulate consumption more strongly than production, whereas the unidentified signaling routes stimulate production more than consumption, leading to no change in membrane potential despite increased respiration rate. The approach allows a quantitative description of the relative importance of signal transduction pathways and the routes by which they activate a specific cellular process. It should be widely applicable. —Krauss, S. , and Brand, M. D. Quantitation of signal transduction. FASEB J. 14, 2581–2588 (2000)
Keyframe-based online object learning and detection

In this paper, we propose a keyframe-based online object learning and detection method. To manage appearance changes of target objects, the proposed method incrementally updates an object database using detection results. One of the major problems in updating the appearance model is that the object model can gradually be degraded by accumulated errors and biased to specific views. To solve this problem, our object model is updated according to the selected keyframes, which not only help memorize important views of target objects, but also prevent the holistic appearance model from overfitting. The database is represented as a graph of the registered images, and the importance of the database images is measured by analyzing the constructed graph. Then, the redundant or less important images are discarded from the database. As a result, the database is efficiently maintained while new views of the objects are gradually added. The experimental results demonstrate that the proposed algorithm efficiently maintains the object database and improves the detection performance compared to previous incremental object learning and detection algorithms.
Brane-antibrane action from boundary string field theory

In this paper we give the boundary string field theory description of brane-antibrane systems. From the world-sheet action of brane-antibrane systems we obtain the tachyon potential and discuss the tachyon condensation exactly. We also find the world-volume action including the gauge fields. Moreover we determine RR-couplings exactly for non-BPS branes and brane-antibranes. These couplings are written by superconnections and correspond to K1(M) and K0(M) for the non-BPS branes and brane-antibranes, respectively. We also show that Myers terms appear if we include the transverse scalars in the boundary sigma model action.
Investigating the Opacity of Verb-Noun Multiword Expression Usages in Context

This study investigates the supervised token-based identification of Multiword Expressions (MWEs). This is an ongoing research to exploit the information contained in the contexts in which different instances of an expression could occur. This information is used to investigate the question of whether an expression is literal or MWE. Lexical and syntactic context features derived from vector representations are shown to be more effective over traditional statistical measures to identify tokens of MWEs.
DIFFERENT TEACHING METHODS IN MUSIC EDUCATION AND ACHIEVEMENT MOTIVATION

The main goal of this paper is to research how different methodological procedures in music education influences achievement motivation in piano students during music teaching. Research is based on Atribution theory elaborated by Bernard Weiner and its adaptation for the music students, made by Edward P. Asmus. We have researched the difference in achievement motivation among piano students from two music schools in Zagreb: the Elly Bašić Music School (EBMS) with a Functional music pedagogy (FMP) curriculum and another music school with the traditional teaching method. Results of the research have shown that EBMS students in comparison with students from standard music school attribute their results achieved to a larger extent to attributing factors: effort, classroom environment and sensitivity to music. Their motivation is stronger since they have a higher ability selfconcept, are more devoted to music, have a better relationship with the music school and with the music school in comparison to other extracurricular activities.
An Alternative String Theory in Twistor Space for N=4 Super-yang-mills

In this letter, an alternative string theory in twistor space is proposed for describing perturbative N=4 super-Yang-Mills theory. Like the recent proposal of Witten, this string theory uses twistor worldsheet variables and has manifest spacetime superconformal invariance. However, in this proposal, tree-level super-Yang-Mills amplitudes come from open string tree amplitudes as opposed to coming from D-instanton contributions.
Numerical study of the linear polarisation resistance technique applied to reinforced concrete for corrosion assessment

The linear polarisation resistance (LPR) technique is increasingly being implemented to assess the corrosion rate of steel reinforcements in concrete. However, a lack of reliability is often observed experimentally. In order to improve the physical comprehension of the LPR technique, FEM simulations were performed. Several measurement devices using annular and rectangular probe geometries were simulated and the numerical experimentation allowed the relevance of RILEM recommendations for on-site measurements to be tested. It was shown that the LPR measurement using annular counter-electrodes with confining devices was a real three-dimensional physical problem and the non-uniform distribution of the polarising current on the steel surface is actually a major source of error since it is not taken into account by the usual protocols. Moreover, it was found that some complexity was induced by the use of guard-rings. La technique de résistance de polarisation linéaire (Rp) est utilisée de plus en plus fréquemment pour évaluer la cinétique de corrosion des aciers dans le béton armé. Cependant, la technique souffre d’un manque de fiabilité. Afin de mieux appréhender la physique de la mesure, des simulations numériques ont été réalisées. Plusieurs dispositifs ont été simulés. Ces expériences numériques ont permis d’éprouver la robustesse du protocole RILEM dédié à la mesure de Rp in situ. Les résultats montrent que les mesures réalisées au moyen de sondes annulaires constituent un problème physique tridimensionnel qui doit être mieux pris en compte par le protocole RILEM. En particulier, la distribution non uniforme du courant polarisant constitue une source d’erreur importante dans la mesure où elle n’est pas considérée dans la recommandation RILEM. Enfin, les simulations ont révélé une forme de complexité supplémentaire induite par l’utilisation d’anneaux de garde pour le confinement du courant polarisant.
Microstructure of cosputter-deposited metal-and oxide-MoS 2 solid lubricant thin films

The effect of cosputtering small amounts of Ni (3%, 9%) and SbOx (20%) on the final microstructure of MoS2 lubricant thin films has been studied using a combination of scanning and transmission electron microscopy imaging, and electron and x-ray diffraction techniques. The early-growth, near-interface microstructure of both MoS2 and 3% Ni–MoS2 cosputtered films is revealed to be a mixture of (002) basal and elongated, large-size (100) and (110) edge islands. Cosputtering with 9% Ni induces a dramatic change in the microstructure, i.e., primarily basal domains with very small isolated regions of edge islands, while cosputtering with 20% SbOx produces films having no long-range order. The results are compared with and are consistent with previously published x-ray absorption fine structure data. The impact of film morphology on tribological performance is discussed.
A Study of Recommender System Techniques

ABSTRACT Many clients like to use the Web to discover product details in the form of online reviews. These reviews are given by other clients and specialists. User-given reviews are becoming more prevalent. Recommender systems provide an important response to the information overload problem as it presents users more practical and personalized information services. Collaborative filtering techniques play vital component in recommender systems as they generate high-quality recommendations by influencing the likings of society of similar users. General Terms Recommender Systems, Algorithms. Keywords Collaborative Filtering, Sparsity problem, Trust network. 1. INTRODUCTION Recommender systems give advice about products, information or services users might be interested in. Recommendation systems generate a ranked list of items on which a user might be interested. Recommendation systems are constructed for movies, books, communities, news, articles etc. They are intelligent applications to assist users in a decision-making process where they want to choose one item amongst a potentially overwhelming set of alternative products or services. Recommender systems are personalized information filtering technology used to either predict whether a particular user will like a particular item or to identify a set of N items that will be of interest to a certain user. It is not necessary that a review is equally useful to all users. The review system allows users to evaluate a review’s support by giving a score that ranges from “not helpful” to “most helpful”. If a particular review is read by all users & found helpful then it can be assumed that new user might appreciate it. Controversial reviews are the reviews that have a variety of conflicting rating (ranking). Controversial review has both passionate followers and motivated enemy without clear majority in either group. The Recommender System uses information from user profile & interaction to tell possible items of concern. It is useful to approximate the degree to which specific user will like a specific product. The Recommender systems are useful in predicting the helpfulness of controversial reviews [1].
Choice of Suture Pattern for Linea Alba Closure

Clinical bottom line Incidence of complications using either a simple continuous or a simple interrupted suture pattern in the linea alba is low if appropriate suture material is chosen and appropriate surgical technique is used. More, well-planned studies with higher power are required before an evidence-based recommendation for one pattern over the other can be made.
Extracting Features for Machine Learning in NTCIR-10 RITE Task

NTCIR-9 RITE task evaluates systems which automatically detect entailment, paraphrase, and contradiction in texts. We developed a preliminary system for the NTCIR-9 RITE task based on rules. In NTCIR-10, we tried machine learning approaches. We transformed the existing rules into features and then added additional syntactic and semantic features for SVM. The straightforward assumption was still kept in NTCIR-10: the relation between two sentences was determined by the different parts between them instead of the identical parts. Therefore, features in NTCIR-9 including sentence lengths, the content of matched keywords, quantities of matched keywords, and their parts of speech together with new features such as parsing tree information, dependency relations, negation words and synonyms were considered. We found that some features were useful for the BC subtask while some help more in the MC subtask.
Semiparametric Bayesian Inference for Multilevel Repeated Measurement Data

Summary We discuss inference for data with repeated measurements at multiple levels. The motivating example is data with blood counts from cancer patients undergoing multiple cycles of chemotherapy, with days nested within cycles. Some inference questions relate to repeated measurements over days within cycle, while other questions are concerned with the dependence across cycles. When the desired inference relates to both levels of repetition, it becomes important to reflect the data structure in the model. We develop a semiparametric Bayesian modeling approach, restricting attention to two levels of repeated measurements. For the top‐level longitudinal sampling model we use random effects to introduce the desired dependence across repeated measurements. We use a nonparametric prior for the random effects distribution. Inference about dependence across second‐level repetition is implemented by the clustering implied in the nonparametric random effects model. Practical use of the model requires that the posterior distribution on the latent random effects be reasonably precise.
Systematic mapping of the literature: social innovation laboratories for the collaborative construction of knowledge from the perspective of open innovation

The objective of this work is to determine the state of the art of social innovation laboratories for the collaborative construction of knowledge from the perspective of open innovation. It employs the methodology of the systematic mapping of the literature using the Science Direct, Springer Open and Google Scholar academic databases. The most significant findings include a tendency for social innovation laboratories using different technologies to socialize knowledge and the use of collaboration tools for the collaborative construction of knowledge. Is has been found that the creation of citizen networks (open social networks, researcher networks or contributor networks) and interdisciplinary work groups is common. Experts in laboratories suggest participating in listening mode since they take into account the experience of those affected and non-experts. Therefore, social innovation labs are spaces that are open to proposals for designing a work plan involving a range of actors to prototype a proposal from the perspective of open innovation.
Caught between ideal and reality: A study on occupational burnout among inside-system legal professionals under the rule-of-law reform in contemporary China

This paper analyzes job burnout of inside-system legal professionals under the rule-of-law reform in China and its possible causes. Social cognitive theory, including cognitive dissonance, expectancy theory, and social comparison theory, provides the analytic framework for this study. The conclusion reveals a relatively high level of job burnout among inside-system legal professionals in China. Further analysis indicates that the individual’s commitment to the rule of law, confidence in the legal reform, and practice of non-rule-of-law in daily work are influential factors affecting his/her job burnout levels. Importantly, the interaction coefficients between these variables are statistically significant, clearly demonstrating that the discrepancy between expectation and reality is one of the root causes of job burnout in the legal profession. The discrepancy causes cognitive dissonance and psychological imbalance. At a theoretical level, this finding opens a new way of examining a particular type of occupational burnout. It shows that under the rule-of-law reform, Chinese inside-system legal professionals exhibit cognitive dissonance between ideals and reality, which constitutes a micro-political psychological basis for organizational change as speculated by neo-institutionalists and, in turn, reveals insights that may help us to understand the legal reform process within the bureaucratic system.
On Kalman filtering with fading wireless channels governed by power control

Abstract We study stochastic stability for Kalman filtering over fading wireless channels where variable channel gains are counteracted by the use of power control to alleviate the effects of packet drops. The Kalman filter and the controller are located at a single gateway which acquires data from the wireless sensors. We establish sufficient conditions which ensure that the Kalman filter covariance matrix is exponentially bounded in norm. The conditions obtained are then used to formulate stabilizing optimal power allocation laws which minimize the total sensor power budget. In deriving the optimal power allocation laws, both statistical channel information and full channel information are considered. The effect of system instability on the power budget is also investigated for both these cases.
Efficient unbiased simulation scheme for SABR stochastic volatility model

The stochastic Alpha Beta Rho stochastic volatility (SABR-SV) model is widely used in the financial industry for the pricing of fixed income instruments. In this paper we develop an unbiased simulation scheme for the SABR-SV model, which deals efficiently with (undesired) possible negative values, the martingale property of the discrete scheme and the discretization bias of commonly used Euler discretization schemes. The proposed algorithm is based the analytic properties of the governing distribution. Experiments with realistic model parameters show that this scheme is robust for interest rate valuation.
Interactive comment on “Assimilation of lidar signals: application to aerosol forecasting in the Mediterranean Basin” by Y. Wang et al

As shown by Roustan et al. (2010) who have performed sensitivity analysis for aerosol and gas-phase concentrations over Europe using the model used in this paper (POLAIR3D/POLYPHEMUS), simulated concentrations of PM are sensitive to boundary conditions (BC). Depending on the global scale model used to provide BC and on the simulated period/year, changing BC could improve or deteriorate aerosol forecasts. If BC are improved, aerosol forecasts may be improved in the simulation without DA, and the impact of DA may be less important. However, depending on period/year and place, changing BC may also deteriorate aerosol forecasts leading to a higher impact of DA. Because simulations of PM strongly depend on other input data, e.g. meteorological fields (Dawson et al., 2007) and emissions (de Meij et al., 2006; Napelenok et al., 2006), the impact of DA may also be more or less important if other input data are changed. The modifications of DA would vary with period/year and place. Therefore, for simplification, this paper presents only one set of input data.
MODEL PREDICTIVE CONTROL OF AUTOMOTIVE POWERTRAINS WITH BACKLASH

Abstract In automotive powertrains, the existence of backlash causes driveability problems, which to some extent are remedied by the engine control system. The control problem has a constrained, minimum-time character, which motivates an investigation of the usability of model predictive control, MPC, in this application. Recent developments in MPC theory make an off-line calculation of the control law possible. This makes MPC more attractive for implementation in fast control loops such as the one under study here. The results indicate that MPC has a potential in this application. However, the off-line computation time is significant, and further robustness investigations are needed.
10 CHAPTER 2 A Short History of Configuration Technologies

Nearly 40-years of configuration technologies motivated us to give this brief overview of the main configuration technological streams. We outline the technological developments in the field starting from the first expert systems of the late 1970s down to today’s configuration solutions. The vastness and intricacies of the configuration field makes it impossible to cover concisely all of its relevant aspects. For the purpose of this overview, we decided to focus on the following four different yet overlapping technological developments: (1) rule-based configurators, (2) early model-based configurators, (3) mainstream configuration environments, and (4) mass customization toolkits. 2.1 Rule-based Configurators Weak Artificial Intelligence (Weak AI) (Searle, 1980) denotes an interpretation of AI in the narrow sense: it supports the accomplishment of specific problem-solving tasks (such as configuration), not encompassing the full range of human cognitive abilities (see Russel and Norvig, 2003). In the line of weak AI (the term was not known at that time), many expert systems were developed in the 1970s. Examples of successful configuration expert systems are (1) R1/XCON (a first version was developed in the late 1970s), a computer configurator (Bachant and McDermott, 1984; McDermott, 1982; Soloway et al., 1987) and (2) VT (vertical transportation), a system for handling the design of elevator systems at the Westinghouse Elevator Company (Marcus et al., 1987). One of the major reasons for applying expert system technologies was the failure of procedural (e.g., FORTRAN-based) approaches to solve the configuration problem. As an example, we focus on the R1/XCON configurator. R1/XCON was an expert system initially implemented by John McDermott on the basis of OPS5 (Forgy, 1981); that is production rules were used for expressing configuration knowledge (see, e.g., Figure 2.1). R1/XCON was developed to support order generation for VAX computer systems (initially for Digital Equipment VAX-11 systems, later for PDP, MICROVAX, and MICRO-PDP). Before R1/XCON was introduced, computers at Digital Equipment (DEC) were configured manually. As a consequence, sales personnel created erroneous, incomplete, and infeasible configurations, which caused enormous overheads and costs. The overall net return to DEC was estimated $40 million dollars per year as the result of the successful delivery of valid and completely configured systems.
Diverse Queries and Feature Type Selection for Plagiarism Discovery Notebook for PAN at CLEF 2013

This paper describes approaches used for the Plagiarism Detection task in PAN 2013 international competition on uncovering plagiarism, authorship, and social software misuse. We present modified three-way search methodology for Source Retrieval subtask and analyse snippet similarity performance. The results show, that presented approach is adaptable in real-world plagiarism situations. For the Detailed Comparison task, we discuss feature type selection and global postprocessing. Resulting performance is significantly better with the described modifications, and further improvement is still possible.