Miracle-dz/UniFAR-FTUs huggingface dataset:
Minimizing Nonconvex Functions for Sparse Vector Reconstruction

In this paper, we develop a novel methodology for minimizing a class of nonconvex (concave on the non-negative orthant) functions for solving an underdetermined linear system of equations As = x when the solution vector s is known a priori to be sparse. The proposed technique is based on locally replacing the original objective function by a quadratic convex function which is easily minimized. The resulting algorithm is iterative and is absolutely converging to a fixed point of the original objective function. For a certain selection of convex objective functions, the class of algorithms called iterative reweighted least squares (IRLS) is shown to be a special case of the proposed methodology. Thus, the proposed algorithms are a generalization and unification of the previous methods. In addition, we also propose a new class of algorithms with better convergence properties compared to the regular IRLS algorithms and, hence, can be considered as enhancements to these algorithms. Since the original objective functions are nonconvex, the proposed algorithm is susceptible to convergence to a local minimum. To alleviate this difficulty, we propose a random perturbation technique that enhances the performance of the proposed algorithm. The numerical results show that the proposed algorithms outperform some of the well-known algorithms that are usually utilized for solving the same problem.
Video mosaic: laying out time in a physical space

Paper video storyboards are still in use by even very experienced video producers with access to the most advanced video editing software. An analysis of the characteristics of paper and on-line editing provide an overlapping but distinct set of benefits (and problems). Paper provides the user with the ability to lay out various temporal sequences over a large spatial area and the ability to quickly sketch, annotate and rearrange the relevant video clips. On-line editing provides users with the ability to generate and store a variety of video arrangements. Video Mosaic provides users with the ability to combine the best of both worlds: elements of a paper video storyboard are used as input to an on-line video editing system to take advantage of the best aspects of each. We developed a Unix and a Macintosh version of Video Mosaic. This paper describes the design of Video Mosaic, compares alternative approaches to creating this type of application, and suggests directions for future work.
On Constructing Shallow Taxonomies from Social Annotations

Tagging in social media system has demonstrated to be a convenient way for users to annotate objects of interest.One reason behind its success obviously because tags can be chosen by users arbitrarily without any topic and specificity constraints. Although tags are free-from keywords, there are some evidences 1 suggesting that, for a particular object type, users tend to use “similar” tag sets. In addition, such tags are in different levels of specificity. This might suggest that there are some hierarchical concepts behind users’ tagging processes. In this paper, we outline a problem in extracting hierarchical concepts from social annotation data and propose a possible solution – a probabilistic generative model that describes tagging processes.
A Simplified Data Processing in MapReduce

For processing and generating large data sets we use MapReduce as a programming model and their associated implementations. A map function is specified by a user to generate a set of intermediate key/value pairs from processes a key/value pair. The warehousing systems existing based MapReduce are not specially optimized for time-based big data analysis applications. Such applications have two characteristics: 1) A continuously generated data are required to be stored persistently for a long period of time; 2) A processed data is used for applications in some time period, for typical queries. For large Data loading and for a high query execution are Time-based big data analytics is required. The current Mapreduce based existing systems solutions do not solve this problem, because of the two requirements are contradictory
Augmenting Points of Interest Recommendations with Music

Recommender systems are personalized information search and decision support tools that can selectively retrieve from large information sources personalized set of items (e.g. news, CD descriptions, or services) that suit the particular preferences of a user. Recommender systems are normally limited in providing recommendations for just one type of information items. But, recently the notion of crossdomain recommender systems has been introduced to denote applications that can reuse knowledge about the users, which is derived in one domain, to provide recommendations in another different domain. A particular kind of cross domain recommendation task consists of selecting simultaneously two items in two different domains and recommending them together because they fit the user preferences and also they fit well together. In this work we show that given a personalized recommendation of points of interests (POIs), the user satisfaction for the itinerary composed by these POIs can be increased by enriching the itinerary presentation with music tracks that match the user’s profile and are coherent with the POIs. We present the results of an online experiment where alternative approaches for matching POIs and music, based on tagging and text matching, have been tested with users.
Fair Is Fair, or Is It? Territorial Identity Triggers Influence Ultimatum Game Behavior

Fairness perception underpins the concept of societal solidarity and is central to regime cohesion, collective identity, and popular legitimacy. The European Union faces challenges on all of these fronts. Perceptions of intergroup (un)fairness and of being "left behind," for example, provided much of the momentum behind the U.K. Brexit decision. Fairness perception is not, however, an objectively reliable measure. In/outgroup alignments, including race and even football team membership, have been shown experimentally to influence individuals' behavior in response to equally fair/unfair monetary offers, even when this behavior is economically irrational. We develop an experimental task, using an adapted ultimatum game design, to examine how this dynamic plays out in the context of multilevel territorial identity systems, such as the European Union (EU), where no straightforward territorial in/outgroup dynamic pertains. We discuss the implications of our findings for understanding complex social-identity effects in multilevel systems. We ask how our findings on differential perceptions of fairness might be built upon to help understand variable citizen perceptions of, for example, the Brexit process and of the outcomes secured by an individuals' "own side" in the negotiations and more generally in relation to psychological attachment to the EU.
Push-recovery stability of biped locomotion

Biped controller design pursues two fundamental goals; simulated walking should look human-like and robust against perturbation while maintaining its balance. Normal gait is a pattern of walking that humans normally adopt in undisturbed situations. It has previously been postulated that normal gait is more energy efficient than abnormal or impaired gaits. However, it is not clear whether normal gait is also superior to abnormal gait patterns with respect to other factors, such as stability. Understanding the correlation between gait and stability is an important aspect of biped controller design. We studied this issue in two sets of experiments with human participants and a simulated biped. The experiments evaluated the degree of resilience to external pushes for various gait patterns. We identified four gait factors that affect the balance-recovery capabilities of both human and simulated walking. We found that crouch gait is significantly more stable than normal gait against lateral push. Walking speed and the timing/magnitude of disturbance also affect gait stability. Our work would provide a potential way to compare the performance of biped controllers by normalizing their output gaits and improve their performance by adjusting these decisive factors.
Bottleneck Estimation for Load Control Gateways-Extended Version 1

Providing Quality of Service (QoS) to inelastic data transmissions in a cost-efficient, highly scalable, and realistic fashion in IP networks remains a challenging research issue. In [14], a new approach for a basic, domain-oriented, reactive QoS systembased on so-called Load Control Gatewayshas been proposed and experimentally evaluated. These load control gateways base their load/admission control decisions on observations of simple, binary marking algorithms executed at internal nodes, which allows the gateways to infer knowledge about the load on each path to peer load control gateways. The original load control system proposal utilizes rather simple, conservative admission control decision criteria. In this paper, we focus on methods to improve the admission control decision by using probability theoretical insights in order to better estimate the load situation of a bottleneck on a given path. This is achieved by making assumptions on the probability distribution of the load state of the nodes and analyzing the effect on the path marking probability. We show that even with benevolent assumptions the exact calculation is mathematically intractable for a larger number of internal nodes and develop a heuristic in the form of a Monte Carlo based algorithm. To illustrate the overall benefit of our approach we give a number of numerical examples which provide a quantitative feeling on how the admission control decision can be improved. Overall, we believe the result of this paper to be an important enhancement of the admission control part of the original load control system which allows to make better usage of resources while at the same time controlling statistically the guarantees provided to inelastic transmissions.
Dynamic Data-Driven Modeling of Pharmaceutical Processes

In many pharmaceutical process operations, first-principle models describing the behavior of the processed powders are difficult to derive or computationally very expensive and thus can be considered as “black-box” processes. Kriging is an efficient data-driven methodology that has been shown previously to predict steady-state operation of black-box processes while providing error estimates for each prediction. In this work, the ability of Kriging to capture the dynamic behavior of processes is evaluated and compared to the performance of dynamic Neural Network (NN) models. Design of Experiment (DoE) concepts are employed to collect the necessary dynamic input–output information that forms the initial multivariate database of the model. The most important feature of the proposed dynamic Kriging methodology is the ability to improve its predictive efficiency as the database is augmented by additional useful information while the process operates. An error tolerance is used in the adaptive procedure, so tha.
Extending Grid-Based Workflow Tools With Patterns/Operators

Many grid applications involve combining computational and data access components into complex workflows. A distinction is generally made between mechanisms to compose components (referred to as build-time functions) and subsequent mechanisms to execute these components on distributed resources (referred to as run-time functions). An approach to supporting such build- and run-time functions using specialist patterns and operators is presented. “Structural” patterns may be treated as meta-components within a workflow system, and used within the composition process. Subsequently, such components may be scheduled for execution using “behavioral” patterns via the enactment process. Application examples are presented to demonstrate how such patterns — and subsequently operators — may be used. Their implementation within the Triana Problem Solving Environment is also described.
The MUSE view of QSO PG1307+085: An elliptical galaxy on the $M_{BH}-\sigma_*$ relation interacting with its group environment

We report deep optical integral-field spectroscopy with the MUSE of the luminous radio-quiet QSO PG1307+085 (z=0.154) obtained during the commissioning of the instrument. Given the high sensitivity and spatial resolution delivered by MUSE, we are able to resolve the compact ($r_e$~1.3") elliptical host galaxy. After careful spectroscopic deblending of the QSO and host galaxy emission, we infer a stellar velocity dispersion of $155\pm19$km/s. This places PG1307+085 local $M_{BH}-\sigma_*$ relation within the intrinsic scatter but offset towards a higher black hole mass with respect to the mean relation. The observations with MUSE also reveal a large extended ENLR around PG1307+085 reaching out to 30kpc. In addition, we detect a faint bridge of ionized gas towards the most massive galaxy of the galaxy group being just 20" (50kpc) away. Previous long-slit spectroscopic observations missed most of these extended features due to a miss-aligned slit. The ionized gas kinematics does not show any evidence for gas outflows on kpc scales despite the high QSO luminosity of $L_\mathrm{bol}>10^{46}$ erg/s. Based on the ionized gas distribution, kinematics and metallicity we discuss the origin of the ENLR with respect to its group environments including minor mergers, ram-pressure stripping or filamentary gas accretion as the most likely scenarios. We conclude that PG1307+085 is a normal elliptical host in terms of the scaling relations, but that the gas is most likely affected by the environment through gravity or ambient pressure. It is possible that the ongoing interaction with the environment, mainly seen in the ionized gas, is also be responsible for driving sufficient gas to feed the black hole at the centre of the galaxy.
HMM-Kalign: a tool for generating sub-optimal HMM alignments

Recent development of strategies using multiple sequence alignments (MSA) or profiles to detect remote homologies between proteins has led to a significant increase in the number of proteins whose structures can be generated by comparative modeling methods. However, prediction of the optimal alignment between these highly divergent homologous proteins remains a difficult issue. We present a tool based on a generalized Viterbi algorithm that generates optimal and sub-optimal alignments between a sequence and a Hidden Markov Model. The tool is implemented as a new function within the HMMER package called hmmkalign.
Effects of Critical Discussions on Middle School Students' Written Historical Arguments.

In this experimental study, 151 middle school students explored 3 historical controversies, first reading and discussing primary source documents in groups, then writing arguments on their own. Students were either randomly assigned to an experimental condition, using argumentative schemes and critical questions as guides during discussions, or to a comparison condition in which a traditional set of questions was used to guide discussions. Students in both conditions read the same historical controversies and used the same text structure heuristic to better compare reading and writing outcomes after students participated in discussion. The findings after instruction indicate comparable reading comprehension and comparable composing skill on general writing measures across conditions. Importantly, the findings also indicate disciplinary benefits for students in the experimental condition in terms of their ability to learn historical content and regarding the quality of students’ historical reasoning in their written arguments. Argument schemes and critical questions appeared particularly helpful in facilitating students’ substantiation of claims and development of rebuttals. (PsycINFO Database Record (c) 2016 APA, all rights reserved)
Research on Chinese ellipsis recovering based on discourse representation theory

This paper presents our research work on Chinese ellipsis recovering based on discourse representation theory (DRT). From various perspectives, our work focuses on how to construct the Chinese DRT and the semantic model. Then it proposes an ellipsis recovering model based on discourse, which selects the most suitable one and fill in the syntactic ellipsis and possible semantic ellipsis. The simulated results show some advantages of the proposed approach based on DRT and potential applications in Chinese oral system and discourse machine understanding
Macroeconomic Effects of Asset‐Price Shocks in a Globalized Financial Market

In this paper, I study a model in which shocks to asset prices affect the real sector of the economy through a credit channel. As financial markets become internationally integrated, the economy becomes less vulnerable to domestic asset‐price shocks, but more vulnerable to foreign asset‐price shocks. To the extent that monetary policy stabilization is feasible and desirable, the globalization of financial markets shifts the focus of monetary policy from domestic asset prices to worldwide asset prices.
Risk factors for chronic transplant dysfunction and cardiovascular disease are related to accumulation of advanced glycation end-products in renal transplant recipients.

BACKGROUND Accumulation of advanced glycation end-products (AGEs) has been implicated in the pathogenesis of chronic transplant dysfunction and cardiovascular disease in renal transplant recipients. We aimed to investigate which factors are associated with tissue AGE accumulation in renal transplant recipients. METHODS The AGE accumulation was assessed using a validated skin-autofluorescence reader (AFR) in 285 consecutive renal transplant recipients (57% male, aged 50+/-12 years) visiting the outpatient clinic at a median (interquartile range) time of 73 (32-143) months after transplantation. Furthermore, various transplant- and recipient-related factors of interest were collected. RESULTS Average skin-autofluorescence of lower arm and leg was 2.7+/-0.8 a.u. Skin-autofluorescence was positively determined by recipient age, systolic blood pressure, smoking, high-sensitivity C-reactive protein, duration of pre-transplant dialysis, and negatively by plasma vitamin C levels, creatinine clearance at baseline, and change in creatinine clearance since one year after transplantation in linear multivariate regression analysis. Together, these factors explained 41% of the variance of skin-autofluorescence. CONCLUSIONS Skin-autofluorescence was associated with several risk factors for cardiovascular disease and chronic renal transplant dysfunction. These results are in line with the hypothesis that AGEs play a role in the pathogenesis of these conditions in renal transplant recipients. Prospective studies are required to investigate whether the AFR can be used as a simple, non-invasive tool to identify and monitor patients at risk for chronic renal transplant dysfunction and cardiovascular disease.
Relationship between Foreign Direct Investment and Per Capita GDP in Nigeria- An Empirical Analysis (1980-2009)

The role of investment has been widely recognized in economic growth process. However domestic investment, especially in developing countries, is usually insufficient to spur growth. Developing countries have therefore embarked on conscious efforts at attracting foreign investments to fill the gaps between domestic and desired investments. This study investigates the relationship between FDI and per capita GDP in Nigeria using a VECM structure. The result reveals the absence of short run causal relationship between FDI and per capita GDP. it also reveals that FDI negatively affects per capita GDP in the long run in Nigeria.
Strict Monotonicity of Sum of Squares Error and Normalized Cut in the Lattice of Clusterings

Sum of Squares Error and Normalized Cut are two widely used clustering functional. It is known their minimum values are monotone with respect to the input number of clusters and this monotonicity does not allow for a simple automatic selection of a correct number of clusters. Here we study monotonicity not just on the minimizers but on the entire clustering lattice. We show the value of Sum of Squares Error is strictly monotone under the strict refinement relation of clusterings and we obtain data-dependent bounds on the difference between the value of a clustering and one of its refinements. Using analogous techniques we show the value of Normalized Cut is strictly anti-monotone. These results imply that even if we restrict our solutions to form a chain of clustering, like the one we get from hierarchical algorithms, we cannot rely on the functional values in order to choose the number of clusters. By using these results we get some data-dependent bounds on the difference of the values of any two clusterings.
Interactions between Entomopathogenic Fungus, Metarhizium anisopliae and Sublethal Doses of Spinosad for Control of House Fly, Musca domestica

Background: Metarhizium anisopliae strain IRAN 437C is one of the most virulent fungal isolates against house fly, Musca domestica. The objective of this study was to determine the interaction of this isolate with sublethal doses of spinosad against housefly. Methods: In adult bioassay, conidia of entomopathogenic fungus were applied as inoculated bait at 105 and 107 spore per gram and spinosad at 0.5, 1 and 1.5 μg (A.I.) per gram bait. In larval bioassay, conidia were applied as combination of spore with larval bedding at 106 and 108 spore per gram and spinosad at sublethals of 0.002, 0.004 and 0.006 μg (AI) per gram medium. Results: Adult mortality was 48% and 72% for fungus alone but ranged from 66–87% and 89–95% in combination treatments of 105 and 107 spore/g with sublethal doses of spinosad respectively. The interaction between 105 spore/g with sublethals exhibited synergistic effect, but in combination of 107 spore in spite of higher mortality, the interaction was additive. There was significant difference in LT50 among various treatments. LT50 values in all combination treatments were smaller than LT50 values in alone ones. Larval mortality was 36% and 69% for fungus alone but ranged from 58%–78% and 81%–100% in combination treatments of 106 and 108 spore/g medium with sublethals of spinosad respectively. The interaction was synergistic in all combination treatments of larvae. Conclusion: The interaction between M. anispliae and spinosad indicated a synergetic effect that increased the house fly mortality as well as reduced the lethal time.
Significance of stop word elimination in meta search engine

Various known meta search engines are built for specific search results. Based on search query meta search engine returns an aggregate list of search results from number of search engines. In this article, significance of stop word elimination for better search results in meta search engine is discussed, and new model of meta search engine is proposed. The output by proposed meta search engine and existing meta search engine like dogpile; with stop words and without stop words; are compared. The result shows that retrieved links in new meta search engine, with and without stop words, is more than 90% same where as by existing meta search engine like dogpile differ with more than 90%.
Programming Models Based on Data Versioning for Dependency-aware Task-based Parallelisation

By using task-based programming models, application developers who are not necessarily experts in parallel programming get access to the potentially high performance of multi-core based computer systems. We have derived a family of task parallel programming models where data dependencies are represented through data versioning. Benefits of using this type of model are that it is easy to represent different types of dependencies and that scheduling decisions can be made locally. Experiments show that a thread parallel shared memory implementation as well as a hybrid thread/MPI distributed memory implementation scale well on a system with 64 cores. Comparing the hybrid implementation with a pure MPI version, the results are comparable for small numbers of cores, but for larger numbers of cores the gain of using the hybrid model is substantial.