Miracle-dz/UniFAR-FTUs huggingface dataset:
Decision-Theoretic Planning with non-Markovian Rewards

A decision process in which rewards depend on history rather than merely on the current state is called a decision process with non-Markovian rewards (NMRDP). In decision-theoretic planning, where many desirable behaviours are more naturally expressed as properties of execution sequences rather than as properties of states, NMRDPs form a more natural model than the commonly adopted fully Markovian decision process (MDP) model. While the more tractable solution methods developed for MDPs do not directly apply in the presence of non-Markovian rewards, a number of solution methods for NMRDPs have been proposed in the literature. These all exploit a compact specification of the non-Markovian reward function in temporal logic, to automatically translate the NMRDP into an equivalent MDP which is solved using efficient MDP solution methods. This paper presents NMRDPP(Non-Markovian Reward Decision Process Planner), a software platform for the development and experimentation of methods for decision-theoretic planning with non-Markovian rewards. The current version of NMRDPP implements, under a single interface, a family of methods based on existing as well as new approaches which we describe in detail. These include dynamic programming, heuristic search, and structured methods. Using NMRDPP, we compare the methods and identify certain problem features that affect their performance. NMRDPP's treatment of non-Markovian rewards is inspired by the treatment of domain-specific search control knowledge in the TLPlan planner, which it incorporates as a special case. In the First International Probabilistic Planning Competition, NMRDPP was able to compete and perform well in both the domain-independent and hand-coded tracks, using search control knowledge in the latter.
Cardiac Myocyte Z-Line Calmodulin Is Mainly RyR2-Bound, and Reduction Is Arrhythmogenic and Occurs in Heart Failure

Rationale: Calmodulin (CaM) associates with cardiac ryanodine receptor type-2 (RyR2) as an important regulator. Defective CaM–RyR2 interaction may occur in heart failure, cardiac hypertrophy, and catecholaminergic polymorphic ventricular tachycardia. However, the in situ binding properties for CaM–RyR2 are unknown. Objective: We sought to measure the in situ binding affinity and kinetics for CaM–RyR2 in normal and heart failure ventricular myocytes, estimate the percentage of Z-line–localized CaM that is RyR2-bound, and test cellular function of defective CaM–RyR2 interaction. Methods and Results: Using fluorescence resonance energy transfer in permeabilized myocytes, we specifically resolved RyR2-bound CaM from other potential binding targets and measured CaM–RyR2 binding affinity in situ (Kd=10–20 nmol/L). Using RyR2ADA/+ knock-in mice, in which half of the CaM–RyR2 binding is suppressed, we estimated that >90% of Z-line CaM is RyR2-bound. Functional tests indicated a higher propensity for Ca2+ wave production and stress-induced ventricular arrhythmia in RyR2ADA/+ mice. In a post–myocardial infarction rat heart failure model, we detected a decrease in the CaM–RyR2 binding affinity (Kd≈51 nmol/L; ≈3-fold increase) and unaltered RyR2 affinity for the FK506-binding protein FKBP12.6 (Kd~0.8 nmol/L). Conclusions: CaM binds to RyR2 with high affinity in cardiac myocytes. Physiologically, CaM is bound to >70% of RyR2 monomers and inhibits sarcoplasmic reticulum Ca2+ release. RyR2 is the major binding site for CaM along the Z-line in cardiomyocytes, and dissociating CaM from RyR2 can cause severe ventricular arrhythmia. In heart failure, RyR2 shows decreased CaM affinity, but unaltered FKBP 12.6 affinity.
Traditional topological indexes vs electronic, geometrical, and combined molecular descriptors in QSAR/QSPR research

A comparison of the performance of molecular descriptors of different types was conducted. The study was concentrated on determining which descriptors are included in the best linear multivariate regression models constructed for modeling various physicochemical properties (melting point, boiling point, refractive index, molar volume, and density) and biological activities (anaesthetic activity, narcotic activity, sweetness intensity). A total of 84 molecular descriptors published over the past 2 decades was included in this study, plus some of their normalized and squared forms. It was shown that, for the estimation of physicochemical properties, the best small regression models with one to four parameters are mainly comprised of "classical" topological indices such as the Randić index, Wiener index, and molecular connectivity indices. For the correlation of biological activity, combinations of topological indices with geometrical descriptors produced regression models of the best quality. In-house developed software was used for generation of the molecular descriptors (the GROUND program) and for the statistical QSAR/QSPR analysis (the GROUNDSTAT program).
Development of an optimized intermolecular potential for sulfur dioxide.

A new force field for sulfur dioxide, capable of predicting accurately the vapor-liquid equilibria, critical properties, vapor pressure, and heats of vaporization is presented. The new force field reproduces the saturated liquid densities, vapor pressures and heats of vaporization to within 0.5, 2, and 2% of experiment, respectively. The predicted critical properties and the normal boiling point are in excellent agreement with experimental results. Pair distribution functions are calculated for the S-S, S-O, and O-O interactions are in close agreement with neutron and X-ray scattering experiments. In addition to the new force field, similar calculations are performed for four SO(2) intermolecular potentials proposed by Sokolic et al. (Sokolic, F. ; Guissani, Y. and Guillot, B. J. Phys. Chem. 1985, 89, 3023], which show that these models work reasonably well near the state point where they were originally parametrized, but large errors in the predicted coexistence properties are displayed at higher and lower temperatures. Comparison of the radial distribution functions show the local structure is only weakly affected by the different force field parameters.
A semantically-based confidence measure for speech recognition

In previous work, we have argued that it is beneficial to find confidence measures (CM's) that are not dependent on use of "side information" from a specific recogniser. Here, we extend this philosophy to include the use of semantic information in estimating the confidence that a word is correct. We are motivated by the observation that sometimes the recogniser outputs a word which can easily be spotted (by humans) as incorrect, because it bears no relation to the semantics of the rest of the decoded sentence. Latent semantic analysis (LSA) was used as a method for estimating semantic "semantic similarity" between words in a text corpus. From these scores, an average semantic similarity of each decoded word to the other decoded words in an utterance could be estimated, and by thresholding this similarity measure, words were tagged as CORRECT or INCORRECT. We benchmarked the performance of this semantic CM against a tried-and-tested CM, the N-best CM. The precision of the semantic CM was inferior to that of N-best when the recall (the number of words considered) was high, but it out-performed N-best for low recall, and a combined classifier showed the benefits of using both techniques. An interesting and unexpected result was that the semantic CM was better at identifying correct words than incorrect words.
European Conference on Information Systems ( ECIS ) 2010 An Early Warning System for Hospital Acquired Pneumonia

Pneumonia is a dangerous, often fatal secondary disease acquired by patients during their stay at Intensive Care Units. ICU patients have scores of data collected on a real time basis. Based on two years of data for a large ICU, we develop an early warning system for the onset of pneumonia that is based on Alternating Decision Trees for supervised learning, Sequential Pattern Mining, and the stacking paradigm to combine the two. Mainly due to decreased stay, the system will save € 180000 in this hospital alone while at the same time increasing the quality and consistent standard of health care. The ultimate system relies on a rather small numeric data base alone and is thus amenable to integration in a treatment protocol and a newly conceived ICU workflow system.
Impact of secondary user communication on security communication of primary user

Cognitive radio network concept has been considered as a promising solution to improve the spectrum utilization. However, it may be vulnerable to security problems as the primary user PU and secondary user SU access the same resource. In this paper, we consider a system model where an eavesdropper EAV illegally listens to the PU communication in the presence of a SU transmitter SU-Tx communicating with a SU receiver SU-Rx. The SU-Tx transmit power is subject to the peak transmit power constraint of the SU and outage probability constraint of the PU. Given this context, the effect of the interference from the SU-Tx to the EAV on the primary system security is investigated. In particular, analytical expressions of the probability of existence of non-zero secrecy capacity and secrecy outage probability of the PU are derived. Moreover, the performance analysis of the secondary network is examined where closed-form expressions of the symbol error probability and achievable rate are presented. Numerical examples are provided to evaluate the impact of the primary system parameters and channel conditions among users on the system performance of secondary and primary networks. Interestingly, our results reveal a fact that the security of the primary network strongly depends on the channel condition of the SU-Tx to the EAV link and the transmit power policy of the SU-Tx. Copyright © 2015 John Wiley & Sons, Ltd.
The Projected Performance Model: Relating Cognitive and Performance Antecedents of Psychological Momentum

Psychological momentum has been an elusive phenomenon in sport psychology research. The present study utilized a two-round free-throw shooting contest between pairs of participants to examine factors which influenced participants' perceptions of momentum and subsequent changes in performance. Factors hypothesized to contribute to perceptions of momentum were divided into three categories of Personal Variables, Situational Variables, and Self-ratings of Performance. Perceptions of momentum could be significantly predicted by both Situational Variables and Self-ratings of Performance. Changes in performance, however, were only significantly predicted by Situational Variables. These findings support the notion that attributions of positive and negative psychological momentum function simply as a labeling process in the evaluation of performance, with little or no effect on subsequent performance. Based on these findings and other research on psychological momentum, a theoretical model (Projected Performance Model) is proposed to conceptualize more clearly fluctuations in performance and their relationship to the construct of psychological momentum.
Choosing Qualitative Research: A Primer for Technology Education Researchers

A number of writers have commented on the dearth of substantive research within the field of technology education, and point to the expansion of its research agenda as a means of strengthening the discipline. Waetjen, in his call for good research in technology education, states that “the plea is to use experimental type research as much as possible” (1992, p. 30). Interestingly, the three areas of research need outlined in his essay would all lend themselves to alternative methodologies, including qualitative methodologies. More recently, others have called for an expansion in the types of research methods used. Of the 220 reports included in Zuga’s review of technology education-related research (1994), only 16 are identified as having used qualitative methods, and Zuga notes that many of those studies were conducted outside the United States. Johnson (1995) suggests that technology educators “engage in research that probes for deeper understanding rather than examining surface features. ” He notes that qualitative methodologies are powerful tools for enhancing our understanding of teaching and learning, and that they have “gained increasing acceptance in recent years” (p. 4). There are compelling reasons for the selection of qualitative methodologies within the educational research arena, yet many people remain unfamiliar with these methods. Researchers trained in the use of quantitative designs face real challenges when called upon to use or teach qualitative research (Stallings, 1995). There is, however, a growing body of literature devoted to qualitative research in education, some of which is synthesized here. The goals of this article are to elaborate on the reasons for choosing qualitative methodologies, and to provide a basic introduction to the features of this type of research.
Autocomplete Textures for 3D Printing

Texture is an essential property of physical objects that affects aesthetics, usability, and functionality. However, designing and applying textures to 3D objects with existing tools remains difficult and time-consuming; it requires proficient 3D modeling skills. To address this, we investigated an auto-completion approach for efficient texture creation that automates the tedious, repetitive process of applying texture while allowing flexible customization. We developed techniques for users to select a target surface, sketch and manipulate a texture with 2D drawings, and then generate 3D printable textures onto an arbitrary curved surface. In a controlled experiment our tool sped texture creation by 80% over conventional tools, a performance gain that is higher with more complex target surfaces. This result confirms that auto-completion is powerful for creating 3D textures.
Initial Positioning Method for Online and Real-Time Dynamic Graph Drawing of Time Varying Data

Microblogging services generate huge histories that suit animated visualization based on graph drawing, but response speeds are insufficient. This paper proposes an effective updating method for the real-time visualization of time varying data. We propose an initial positioning method by combining Additional Edge Resizing (AER) with Sorted Sequential Barycenter Merging (SSBM). AER resizes edges between existing nodes when new edges are added before updating the visualization. SSBM initially positions multiple new nodes sequentially through priority based on the degree of connections to the existing graph. The proposed method prevents a decrease in readability at data update and achieves fast convergence with high accuracy. Quantitative and qualitative evaluations using the energy function and RMSE are detailed along with some visualization results. A graph drawing tool based on HTML5 is also introduced as an implementation of the proposed method and present some use cases for twitter data.
Sparse coding with a global connectivity constraint

Basis pursuit via sparse coding techniques have generally enforced sparseness by using L1-type norms on the coefficients of the bases. When applied to natural scenes these algorithms famously retrieve the Gabor-like basis functions of the primary visual cortex (V1) of the mammalian brain. In this paper, inspired further by the architecture of the brain, we propose a technique that not only retrieves the Gabor basis but does so respecting global power-law type connectivity patterns. Such global constraints are beneficial from a biological perspective in terms of efficient wiring, robustness etc. We draw on the similarity between sparse coding and neural networks to formulate the problem and impose such global connectivity patterns.
Surface properties of right side-out plasma membrane vesicles isolated from barley roots and leaves.

Highly purified plasma membrane vesicles were obtained from roots and leaves of 7-day-old light-grown barley (Hordeum vulgare L. cv Kristina) seedlings by partitioning of crude microsomal fractions in a dextran-polyethylene glycol two-phase system. Sodium dodecylsulfate polyacrylamide gel electrophoresis showed the polypeptide composition of plasma membranes from the two organs to be qualitatively similar, but with different relative amounts of some of the polypeptides. Between 80 and 100% of the K(+),Mg(2+)-ATPase activity was latent indicating that the vesicles were sealed and right side-out. The isoelectric points of the outer surface of root and leaf plasma membranes as determined by cross-partitioning were similar and quite acidic-about pH 3.6. In contrast, the net negative surface charge density at pH 7.0 as measured by 9-aminoacridine fluorescence differed significantly, being -29 mC.m(-2) for the leaf plasma membrane and only -19 mC.m(-2) for the root plasma membrane. As isolated, both types of plasma membrane vesicles had Ca(2+) and Mg(2+) bound to the outer surface as shown by the combined use of chelators and 9-aminoacridine fluorescence; however, the leaf plasma membrane had a relatively higher proportion of Ca(2+) bound (0.57) than did the root plasma membrane (0.45). This difference probably reflects differences in the in vivo conditions as no chelator was present during the isolation procedure. Also Ni(2+) could bind to the root vesicles as indicated by the effect of Ni(2+) on 9-aminoacridine fluorescence, and by the binding of (63)Ni(2+) (44 nanomoles bound per milligram protein) at 100 micromolar NiCl(2).
The Related Techniques of Content-Based Image Retrieval

With the popularity of the network and development of multimedia technology, the traditional information retrieval techniques do not meet the users¿ demand. Recently, the content-based image retrieval has become the hot topic and the techniques of content-based image retrieval have been achieved great development. In this paper, the basic components of content-based image retrieval system are introduced. Image retrieval methods based on color, texture, shape and semantic image are discussed, analyzed and compared. The semantic-based image retrieval is a better way to solve the ¿semantic gap¿ problem, so the semantic-based image retrieval method is stressed in this paper. Other related techniques such as relevance feedback and performance evaluation also discussed. In the end of paper the problems and challenges are proposed.
Selecting the Right Algorithm

Computer scientists always strive to find better and faster algorithms for any computational problem. It is usually true that programmers and/or users come across a plethora of different algorithms when looking to solve a particular problem efficiently. Each one of these algorithms might offer different guarantees and properties, but it is unlikely that a single one of them is the best (fastest) in all possible cases. So, the question that the programmer/user typically faces is: “Which algorithm should I select? ” This question is largely due to the uncertainty in the input space, the inner workings of the algorithm (especially true for randomized algorithms), and the hardware characteristics. It’s hard to know in advance what kind of inputs will be provided, how exactly the computation will proceed, or even how efficiently the underlying hardware will support the needs of the different algorithms. Sometimes, a careful study can reveal that committing to a particular algorithm is better than committing to any of the other algorithms, but is this the best we can do? What if uncertainty is explicitly taken into account and the right decision is made dynamically on an instance-by-instance basis? To make the discussion more concrete, consider, for example, the problem of sorting. Why would you ever choose MergeSort or InsertionSort when you know that QuickSort is in general the fastest algorithm for sorting? That might be true to some extent, but it seems that if you allow for collaboration of these three “competitors”, the outcome can be beneficial. Think of this algorithm selection problem(Rice 1976) as a decision problem: “Which algorithm should I run whenever a new instance is presented? ”The fact that two of these algorithms are recursive makes the problem even more interesting. Every time a recursive call is made, you can ask the same question: “Which algorithm should I choose for the current subproblem? ”. Nothing really dictates that you have to use the same algorithm again and again throughout the recursion. How, then, can you optimize this sequence (or better, tree) of decisions? On what ground is each decision based?
HvALMT1 from barley is involved in the transport of organic anions

Members of the ALMT gene family contribute to the Al3+ resistance of several plant species by facilitating malate efflux from root cells. The first member of this family to be cloned and characterized, TaALMT1, is responsible for most of the natural variation of Al3+ resistance in wheat. The current study describes the isolation and characterization of HvALMT1, the barley gene with the greatest sequence similarity to TaALMT1. HvALMT1 is located on chromosome 2H which has not been associated with Al3+ resistance in barley. The relatively low levels of HvALMT1 expression detected in root and shoot tissues were independent of external aluminium or phosphorus supply. Transgenic barley plants transformed with the HvALMT1 promoter fused to the green fluorescent protein (GFP) indicated that expression of HvALMT1 was relatively high in stomatal guard cells and in root tissues containing expanding cells. GFP fused to the C-terminus of the full HvALMT1 protein localized to the plasma membrane and motile vesicles within the cytoplasm. HvALMT1 conferred both inward and outward currents when expressed in Xenopus laevis oocytes that were bathed in a range of anions including malate. Both malate uptake and efflux were confirmed in oocyte assays using [14C]malate as a radiotracer. It is suggested that HvALMT1 functions as an anion channel to facilitate organic anion transport in stomatal function and expanding cells.
Multi-product Offshoring Multi-product O¤shoring

In this paper, we incorporate o¤shoring of labor-intensive goods in a model with multi-product rms, and explore its implications in partial and general oligopolistic equilibrium. We identify important aspects of this phenomenon and argue that improvements in o¤shoring opportunities can a¤ect the geographic organization of a rm and its product range. Multi-product rms internalize supply linkages (exible manufacturing) and demand linkages (cannibalization e¤ect). In partial equilibrium, we nd that more products are produced o¤shore on a larger scale and rms expand their product range with better prospects for o¤shoring. We identify the cannibalization e¤ect as an important transmission mechanism within multi-product rms and show that the latter e¤ect hits domestic labor demand in addition to the well-known relocation e¤ect. Interestingly in general equilibrium these e¤ects lead to adjustments in domestic factor prices and may cause a partial re-relocation of product lines. Keywords: Multi-Product Firms, Cannibalization E¤ect, Product Range, E¢ ciencyseeking O¤shoring, General Oligopolistic Equilibrium. JEL Classi cation: F12, F 23, L23 We thank Daniel Baumgarten, Lisandra Flach, J. Peter Neary, Tobias Seidel, Mirjam Wuggenig, Stephen Yeaple, and participants in International Economics Workshop in Göttingen 2012, ETSG 2012 in Leuven, O¤shoring and International Production Conference in Tuebingen 2013, Midwest Economic Theory and International Trade Meetings in Ann Arbor 2013, EGIT conference at CESifo 2014, and SFB TR 15 conference in Mannheim 2014. yDepartment of Economics, D-80539 Muenchen, Germany; tel. : (+49) 2180 5824 ; e-mail: Carsten.Eckel@econ.lmu. de; internet: http://www.intecon. vwl.uni-muenchen.de/. zCorresponding author. Department of Economics, D-80539 Muenchen, Germany; tel. : (+49) 218