Miracle-dz/UniFAR-FTUs huggingface dataset:
Metrics from the Jazz Repository

This paper describes the extraction of source code metrics from the Jazz repository and the systematic application of data mining techniques to identify the most useful of those metrics for predicting the success or failure of an attempt to construct a working instance of the software product. Results are presented from a study using the J48 classification method used in conjunction with a number of attribute selection strategies applied to a set of source code metrics. These strategies involve the investigation of differing slices of code from the version control system and the cross-dataset classification of the various significant metrics in an attempt to work around the multicollinearity implicit in the available data. The results indicate that only a relatively small number of the available software metrics that have been considered have any significance for predicting the outcome of a build. These significant metrics are outlined and implication of the results discussed, particularly the relative difficulty of being able to predict failed build attempts.
Antioxidant enzymes as redox-based biomarkers: a brief review

The field of redox proteomics focuses to a large extent on analyzing cysteine oxidation in proteins under different experimental conditions and states of diseases. The identification and localization of oxidized cysteines within the cellular milieu is critical for understanding the redox regulation of proteins under physiological and pathophysiological conditions, and it will in turn provide important information that are potentially useful for the development of novel strategies in the treatment and prevention of diseases associated with oxidative stress. Antioxidant enzymes that catalyze oxidation/reduction processes are able to serve as redox biomarkers in various human diseases, and they are key regulators controlling the redox state of functional proteins. Redox regulators with antioxidant properties related to active mediators, cellular organelles, and the surrounding environments are all connected within a network and are involved in diseases related to redox imbalance including cancer, ischemia/reperfusion injury, neurodegenerative diseases, as well as normal aging. In this review, we will briefly look at the selected aspects of oxidative thiol modification in antioxidant enzymes and thiol oxidation in proteins affected by redox control of antioxidant enzymes and their relation to disease. [BMB Reports 2015; 48(4): 200-208]
A Bright Idea for Measuring Economic Growth.

The quantity of human-generated light visible from outer space reflects variation in both population density and income per capita. In this paper we explore the usefulness of the change in visible light as a measure of GDP growth. We discuss the data, and then present a statistical framework that uses lights growth to augment existing income growth measures, assuming that measurement errors in the two series are uncorrelated. For some countries with very poor income measurement, we significantly revise estimates of growth. Our technique also produces growth estimates for cities or regions where no other data are available.
Picking Out Good Dishes from Yelp

Sifting through restaurant reviews on Yelp to find good dishes can be quite difficult, especially when reviewers use colloquial terms for the dishes instead of actual menu names. However, this can be done programmatically. In this paper, we introduce several methods to accurately match food items mentioned in reviews with the official menu item name. These include string-matching algorithms such as ExactMatch and PartialMatch, as well as a support vector machine matcher, SVMMatch. We achieve an F1 score of 0.72 with the SVM and a recall of 0.84 with PartialMatch by comparing our matches with annotated results. We also use annotations for sentiment analysis on food mentions and find that most dishes are rated positively by their reviewer. Finally, we do location analyses which reveals that of the seven cities in the data set, reviewers tend to rate Chicago dishes higher.
Cytoplasmic Linker Proteins Regulate Neuronal Polarization through Microtubule and Growth Cone Dynamics

Axon formation is a hallmark of initial neuronal polarization. This process is thought to be regulated by enhanced microtubule stability in the subsequent axon and changes in actin dynamics in the future axonal growth cone. Here, we show that the microtubule end-binding proteins cytoplasmic linker protein (CLIP)-115 and CLIP-170 were enriched in the axonal growth cone and extended into the actin-rich domain of the growth cone. CLIPs were necessary for axon formation and sufficient to induce an axon. The regulation of axonal microtubule stabilization by CLIPs enabled the protrusion of microtubules into the leading edge of the axonal growth cone. Moreover, CLIPs positively regulated growth cone dynamics and restrained actin arc formation, which was necessary for axon growth. In fact, in neurons without CLIP activity, axon formation was restored by actin destabilization or myosin II inhibition. Together, our data suggest that CLIPs enable neuronal polarization by controlling the stabilization of microtubules and growth cone dynamics.
Solving motion planning problems by iterative relaxation of constraints

This dissertation presents a new approach to improve automated motion planners. Automatic motion planning has application in many areas such as robotics, virtual reality systems, and computer-aided design. Surprisingly, a single class of planners, called probabilistic roadmap methods (PRMs), have proven effective on problems from all these domains. Strengths of PRMs are simplicity and efficiency, even in high-dimensional configuration spaces. Nevertheless, PRMs are not as effective in environments where the solution path requires the robot to pass through a narrow passage. In this dissertation, we suggest a hierarchical strategy addressing this problem where we first simplify the problem by relaxing some feasibility constraints, solve the easier version of the problem, and then use that solution to help find a solution for the harder problem. We show how this strategy can be applied to (i) “virtual prototype” analysis, where the goal is to find a removal path for one part (the robot) from an assembly of other parts (obstacles), (ii) “ligand binding,” where we generate candidate binding sites for a ligand in a large protein molecule, and (iii) “deformable objects,” where the robot can deform itself to avoid collision while following a path.
Research on Modeling of Multiparty Trust Negotiation Based on Coloured Petri-net in P2P Network

Current academic research about automated trust negotiation is mainly focused on duplex sensitive information disclosure. However, real world automated trust negotiation often involve more than two parties. Decomposition is insufficient to reduce an automated multiparty authorization into standalone two-party trust negotiations, because individual negotiations may depend on one another, and therefore need to be interleaved in a certain order for the overall negotiation to succeed. In this paper, we define an extended DARCL policy language, and propose a new modeling method of multiparty trust negotiation based on Coloured Petri-net in P2P network environment.
Womb Grammars : Constraint Solving for Grammar Induction

We present Womb Grammars, a novel constraint-based framework implemented in CHRG and particularly useful for inducing, from known linguistic constraints that describe phrases in a language called the source, the linguistic constraints that describe phrases in another language, called the target. We present as well an application that uses as source an existing language fairly related to the target. Next we propose and motivate an intriguing research thread that uses as source language a (non-natural but coupled with our framework, generatively very powerful) universal language of our own device. Finally, we discuss further ramifications of our work.
Improved active clamp for secondary circuits

The paper describes improvements to an active clamp for secondary circuits in isolated converter topologies. The active clamp provides both voltage clamping of the secondary diodes and the recycling of diode reverse recovery energy stored in the leakage inductance of the transformer secondary winding. An isolated winding on the recycling circuit permits variation in the location of the output choke, which is shown to provide a possible 10 dB reduction of common mode noise. Results from a 700 W telecommunications rectifier using a planar transformer are presented.
Framework for Benefits Realization in e- Government Interoperability Efforts

The purpose of this position paper is to generate support for research into benefits realization in egovernment interoperability projects. As e-Government practice matures, one can observe a shift in focus towards quality management, evaluation and ultimately a quest for realized benefits. Hence, Norway, like many countries, is now attempting to introduce practices related to benefits management or benefits realization (BM/BR). However, BM is in many ways an immature field with limited studies available.
Keyword Location in Noisy Document Images

It may be difficult to locate keywords in noisy document images because of degraded OCR performance. A new technique for word image matching has the potential to select those. word images in a document that . represent potential keywords and to generate improved prototypes for those keywords. No explicit recognition is pe~formed in this process, but better OCR performance will occur on the improved prototypes' than • would occur on any of the isolated" words. The proposed method for keyword selection and recognition is best suited for document indexing in an image-based document retrieval system. This paper presents an algorithm for word image clustering and discusses how it is applied to locate groups of equivalent word images in a document. Improved prototypes are generated for clusters that represent potential keywords. The results of applying the algorithm to an article in the Brown Corpus are given. The keywdrds chosen by this' approach and those chosen from the ASCII text of the article by a conventional keyword selection methodology are compared. The potential for improvementin recognition performance on those keywords is also demonstrated.
Implementing Marketable Emissions Permits

The Environmental Protection Agency is introducing bubbles, offsets, and banks as a way of controlling pollution with market incentives to obtain standards for each source and guide the reallocation of emissions. The new method is not a true market because polluters must go through the permitting procedure in order to trade emission allowances. This study examines whether an efficient market without source-by-source review is feasible. It considers the importance of enough participants, competitiveness, sensitivity to geographic emission patterns, and trading flexibility to sustain marketable permits. The design features that address these problems are permit life, market definition, market initiation, and market operation. A stable permit market eliminates some of the uncertainties in decision making because it allows firms to select a preferred level of risk. 9 references. (DCK)
Comparing Breast Screening Protocols: Inserting Catch Trials Does Not Improve Sensitivity over Double Screening

Breast screening is an important tool for the early detection of breast cancers. However, tumours are typically present in less than 1% of mammograms. This low prevalence could cause radiologists to detect fewer tumours than they otherwise would, an issue known as the prevalence effect. The aim of our study was to investigate a novel breast screening protocol, designed to decrease the number of tumours missed by radiologists, without increasing their workload. We ran two laboratory-based experiments to assess the degree to which the novel protocol, called the catch trial (CT) protocol, resulted in greater sensitivity (d’) than the double screener protocol (DS), currently utilised in Australia. In our first experiment we found evidence that the CT protocol resulted in a criterion shift relative to the DS protocol but the evidence that sensitivity was greater in the CT protocol relative to the DS protocol was less clear. A second experiment, using more realistic stimuli that were more representative of actual tumours, also failed to find convincing evidence that sensitivity was greater in the CT protocol than in the DS protocol. This experiment instead found that both the hit rate and the false alarm rate increased in the CT protocol relative to the DS protocol. So while there was again evidence that the CT protocol induced a criterion shift, the sensitivity appeared to be approximately the same in both protocols. Our results suggest the CT protocol is unlikely to result in an improvement in sensitivity over the DS protocol, so we cannot recommend that it be trialled in a clinical setting.
Regulation of branching dynamics by axon-intrinsic asymmetries in Tyrosine Kinase Receptor signaling

Axonal branching allows a neuron to connect to several targets, increasing neuronal circuit complexity. While axonal branching is well described, the mechanisms that control it remain largely unknown. We find that in the Drosophila CNS branches develop through a process of excessive growth followed by pruning. In vivo high-resolution live imaging of developing brains as well as loss and gain of function experiments show that activation of Epidermal Growth Factor Receptor (EGFR) is necessary for branch dynamics and the final branching pattern. Live imaging also reveals that intrinsic asymmetry in EGFR localization regulates the balance between dynamic and static filopodia. Elimination of signaling asymmetry by either loss or gain of EGFR function results in reduced dynamics leading to excessive branch formation. In summary, we propose that the dynamic process of axon branch development is mediated by differential local distribution of signaling receptors. DOI: http://dx.doi. org/10.7554/eLife.01699. 001
Automated dimensionality reduction in EEG based Brain Computer Interface

A simple method is developed for selecting effective channels and feature dimensions automatically at the training stage of BCI systems. The method is applied on feature vectors constructed with all the EEG channels used for recording. Performance was evaluated with EEG data which was preprocessed by band pass filtering and feature vectors constructed by band powers. The classification method used in the evaluation is k Nearest Neighbor classifier, which is sensitive to number of dimensions in the feature vectors. It was found that new method can effectively select features and reduce channels and thereby improve accuracy and efficiency of BCI systems.
High-level semantic video annotation based on 3D scene structure analysis

The application of 3D scene reconstruction techniques in the area of automatic semantic annotation, search and retrieval of unedited video footage has become an interesting field of research for some specific type of video content. Usually static key-frames extracted from a sequence of images are analyzed in order to annotate the content. In the case of a moving camera, the temporal properties of the video can be exploited as well. Based on state of the art camera self calibration techniques a powerful analysis chain has been developed, which allows annotation with regard to specific properties of the 3D scene structure. It is demonstrated, that the reconstructed 3D scene information can be used to generate, accurate low level scene descriptors as well as meaningful medium and high level semantic information. The specific frame-based properties of the triangulated 3D scene contain a lot of potential for semantic annotation, which goes beyond standard 2D scene descriptors.
Linking Social Media with Open Innovation: An Intelligent Model

A hybrid intelligent model for linking social media with open innovation strategies, processes and diffusion is proposed and discussed in this paper. In order to deal with the various facets or properties of the open innovation problem, we recommend and present a new paradigm and framework for integrating the strengths or advantages of intelligent software agents, fuzzy logic, expert systems, complex adaptive system theory, the analytic hierarchy process, simulation technique, and hybrid intelligent system method. The theoretical underpinning and rationale for the hybrid framework are provided. In addition, the effectiveness and efficiency of using social media, artificial intelligence, groupware and group decision support systems, and other decision support techniques and technologies in open innovation management are explored. Furthermore, research hypotheses on this topic are formulated.
THE PROBABILISTIC METHOD, RANDOM GRAPHS AND STEIN’S METHOD

The Probabilistic Method has been initiated by Paul Erdős [6] in order to prove the existence of certain combinatorial objects. The principle idea is to define a proper probability distribution on a class of (discrete) objects and to show that the probability of a certain property is positive. Of course this also proves that there exists such an object with this property. We will apply this approach to various problems on random graphs. However, the main goal of this course is to give an introduction to Stein’s method that proves asymptotic normality for sums of (in some sense) weakly dependent random variables. This method has turned out to be very successful, in particular in random graph problems. There is vast literature on these topics. We just mention few books that are exclusively devoted to them [1, 5, 9, 10].
Progress in Nonprehensile Manipulation

This paper reviews my recent research in robotic manipulation and speculates on potentially fruitful directions for future work. My recent work is focused on nonprehensile manipulation: manipulating objects without grasping them. In particular, the paper surveys work on a single joint robot that orients parts on a conveyor belt; a robot that uses dynamics to snatch, roll, or throw objects; hitting things to position them; manipulating things whose shapes are not completely known; and integration of manipulation with locomotion. In the future, a broad view of robotics will allow us to focus on fundamental principles and at the same time address a variety of new applications.
On the Resilience of Bipartite Networks

Motivated by problems modeling the spread of infections in networks, in this paper we explore which bipartite graphs are most resilient to widespread infections under various parameter settings. Namely, we study bipartite networks with a requirement of a minimum degree d on one side under an independent infection, independent transmission model. We completely characterize the optimal graphs in the case $d =1$, which already produces non-trivial behavior, and we give extremal results for the more general cases. We show that in the case $d=2$, surprisingly, the optimally resilient set of graphs includes a graph that is not one of the two “extremes” found in the case $d=1$. Then, we briefly examine the case where we force a connectivity requirement instead of a one-sided degree requirement and again, we find that the set of the most resilient graphs contains more than the two “extremes. ” We also show that determining the subgraph of an arbitrary bipartite graph most resilient to infection is NP-hard for any one-sided minimal degree $d\ge 1$.
Economic development, environmental regulation, and the international migration of toxic industrial pollution : 1960-88

Several previous studies have asked whether environmental controls imposed in the industrial economies are diverting investments in pollution-intensive activities off-shore. Broadly, these studies conclude that direct investment does not appear to be stimulated by such regulations, partly because the cost of emission controls is generally a tiny fraction of operating costs. Yet direct investment reflects only part of what may be happening to world production patterns. Technology transfers may occur with no simultaneous direct investments, and production may readily shift toward a different global distribution without either direct investment or technology transfer. The authors attempt a general test of the displacement hypothesis, developing time series estimates of manufacturing pollution intensity for a large sample of developed and developing countries between 1960 and 1988. Among their conclusions: As a result of shifts in industrial composition, total manufacturing emissions relative to GDP grow faster than GDP at lower levels of per capita income and slower than GDP at higher levels of income. This happens because manufacturing has a declining share of GDP at higher income levels, not because of any shift toward a cleaner mix of manufacturing activities. The more rapidly growing high-income countries have actually enjoyed negative growth in toxic intensity of their manufacturing mix. Stricter regulation of pollution-intensive production in the OECD countries appears to have led to significant locational displacement, with consequent acceleration of industrial pollution intensity in developing countries. The poorest economies seem to have the highest growth in toxic intensity. One cannot, of course, be certain of the causal connection. Pollution intensity has grown most rapidly in developing economies that are relatively closed to world market forces. Relatively closed, fast-growing economies experienced rapid structural transitions toward greater toxic intensity. The opposite seems to have been true for more open economies.
Large Equivalent Width Lyα line Emission at z=4.5: Young Galaxies in a Young Universe?

The Large Area Lyman Alpha survey has found ≈150 Lyα emitters at z = 4.5. While stellar models predict a maximum Lyα equivalent width (EW) of 240 Å, 60% of the Lyα emitters have EWs exceeding this value. We attempt to model the observed EW distribution by combining stellar population models with an extrapolation of a Lyman break galaxy luminosity function at z = 4, incorporating observational selection effects and Malmquist bias. To reproduce the high EWs seen in the sample, we need to postulate a stellar initial mass function with an extreme slope of α = 0.5 (instead of 2.35), zero-metallicity stars, or narrow-line active galactic nuclei (AGNs). Not all the high-EW sources can be AGNs without exceeding the X-ray background or postulating a very steep redshift evolution. Only 7.5%-15% of galaxies need to show Lyα emission to explain the observed number counts. This raises the possibility either that star formation in high-redshift galaxies is episodic or that the Lyα galaxies we are seeing are the youngest 7.5%-15% and that Lyα is strongly quenched by dust at about 107 yr of age.
Modifying CLJP to select grid hierarchies with lower operator complexities and better performance

Algebraic multigrid (AMG) is an efficient algorithm for solving certain types of large, sparse linear systems. For solving very large problems with AMG it becomes necessary to use parallel algorithms. Coarse grid selection algorithms such as CLJP were created to parallelize the setup phase of AMG. For some problems, such as those discretized on structured meshes, CLJP tends to select coarse grids with more nodes than alternative coarsening algorithms. In this paper, the cause for the selection of too many coarse nodes by CLJP is examined, and a new technique which lowers the operator complexities generated by CLJP is introduced. To validate the new method, the modified CLJP is compared to other coarsening algorithms for large‐scale problems. Copyright © 2006 John Wiley & Sons, Ltd.