Miracle-dz/UniFAR-FTUs huggingface dataset:
A Broad Alliance of Civil Society Organizations on Climate Change Mitigation: Political Strength or Legitimizing Support?

ABSTRACT One hundred and one very different organizations joined together prior to the election for the Norwegian parliament in 2013 in order to make climate change mitigation the most important issue in the election campaign. The alliance (CE2013) agreed on six political demands relating to mitigation. In this article, we categorize the 101 organizations and discuss their identity and objectives according to these demands. The analysis demonstrates that even though a broad variety of organizations joined the campaign, their commitment was rather weak. Few of the organizations justify their involvement in CE2013 by all six political demands, hence demonstrating that climate change mitigation is a valence issue.
Activation and activities of the p53 tumour suppressor protein

The p53 tumour suppressor protein inhibits malignant progression by mediating cell cycle arrest, apoptosis or repair following cellular stress. One of the major regulators of p53 function is the MDM2 protein, and multiple forms of cellular stress activate p53 by inhibiting the MDM2-mediated degradation of p53. Mutations in p53, or disruption of the pathways that allow activation of p53, seem to be a general feature of all cancers. Here we review recent advances in our understanding of the pathways that regulate p53 and the pathways that are induced by p53, as well as their implications for cancer therapy. © 2001 Cancer Research Campaign
How I Stopped Worrying about the Twitter Archive at the Library of Congress and Learned to Build a Little One for Myself

Twitter is among the commonest sources of data employed in social media research mainly because of its convenient APIs to collect tweets. However, most researchers do not have access to the expensive Firehose and Twitter Historical Archive, and they must rely on data collected with free APIs whose representativeness has been questioned. In 2010 the Library of Congress announced an agreement with Twitter to provide researchers access to the whole Twitter Archive. However, such a task proved to be daunting and, at the moment of this writing, no researcher has had the opportunity to access such materials. Still, there have been experiences that proved that smaller searchable archives are feasible and, therefore, amenable for academics to build with relatively little resources. In this paper I describe my efforts to build one of such archives, covering the first three years of Twitter (actually from March 2006 to July 2009) and containing 1.48 billion tweets. If you carefully follow my directions you may have your very own little Twitter Historical Archive and you may forget about paying for historical tweets. Please note that to achieve that you should be proficient in some programming language, knowable about Twitter APIs, and have some basic knowledge on ElasticSearch; moreover, you may very well get disappointed by the quality of the contents of the final dataset.
Patients with Congenital Systemic-to-Pulmonary Shunts and Increased Pulmonary Vascular Resistance: What Predicts Postoperative Survival?

Background We carried out a retrospective data review of patients with systemic to pulmonary shunts that underwent surgical repair between February 1990 and February 2012 in order to assess preoperative pulmonary vascular dynamic risk factors for predicting early and late deaths due presumably to pulmonary vascular disease. Methods and Results A total of 1024 cases of congenital systemic-to-pulmonary shunt and advanced pulmonary vascular disease beyond infancy and early childhood were closed surgically. The mean follow up duration was 8.5±5.5 (range 0.7 to 20) years. Sixty-one in-hospital deaths (5.96%, 61/1024) occurred after the shunt closure procedure and there were 46 late deaths, yielding 107 total deaths. We analyzed preoperative pulmonary vascular resistance index (PVRI), pulmonary vascular resistance index on pure oxygen challenge (PVRIO), difference between PVRI and PVRIO (PVRID), Qp∶Qs, and Rp∶Rs as individual risk predictors. The results showed that these individual factors all predicted in-hospital death and total death with PVRIO showing better performance than other risk factors. A multivariable Cox regression model was built,and suggested that PVRID and Qp∶Qs were informative factors for predicting survival time from late death and closure of congenital septal defects was safe with a PVRIO<10.3 WU.m2 and PVRID>7.3 WU.m2 on 100% oxygen. Conclusions All 4 variables, PVRI, PVRIO, PVRID and Qp∶Qs, should be considered in deciding surgical closure of congenital septal defects and a PVRIO<10.3 WU.m2 and PVRID>7.3 WU.m2 on 100% oxygen are associated with a favorable risk benefit profile for the procedure.
Recurrent Backpropagation and the Dynamical Approach to Adaptive Neural Computation

Error backpropagation in feedforward neural network models is a popular learning algorithm that has its roots in nonlinear estimation and optimization. It is being used routinely to calculate error gradients in nonlinear systems with hundreds of thousands of parameters. However, the classical architecture for backpropagation has severe restrictions. The extension of backpropagation to networks with recurrent connections will be reviewed. It is now possible to efficiently compute the error gradients for networks that have temporal dynamics, which opens applications to a host of problems in systems identification and control.
Predicting the Performance of Bowlers in IPL: An Application of Artificial Neural Network

Application of data mining tools is often used in professional sports for evaluating players/teams’ performance. Cricket is one of those sports where a large amount of numerical information is generated in every game. The game of cricket got a new dimension in April 2008, when Board of Control for Cricket in India (BCCI) initiated the Indian Premier League(IPL). It is a franchise based Twenty20 cricket tournament where teams are formed by competitive bidding from a collection of Indian and International players. Since, valuations of the players are determined through auction, so performance of individual player is always under scanner. The objective of this study is to analyze and predict the performance of bowlers in IPL, using artificial neural network. Based on the performance of bowlers in the first three seasons of IPL, the paper tries to predict the performances of those bowlers who entered in the league in its fourth season as their maiden IPL venture. The performances of these bowlers in IPL-IV are predicted, and the external validity of the model is tested using their actual performance in IPL-IV. This prediction can help the franchises to decide which bowler they should target for their team.
A preliminary study of information collection in a mobile sensor network

Mobile sensor networks are desirable in a variety of application scenarios, in which information collection is no doubt of great importance. In this paper, we present a mobile sensor network architecture consisting of a potentially large number of mobile sensors and a single or multiple stationary sink nodes for sensing information collection. We formulate a distinct coverage measurement problem in term of sensing information collection; we study the relevant performance and examine the effect from a variety of relevant factors through extensive simulations. We demonstrate that the performance is not only affected by the sensor mobility and the transmission range between mobile sensors and sink node(s), but also by the distribution of mobile sensors and the number and locations of sink nodes. Based on the observation and analysis, we also provide some preliminary understandings and implications for improving the information collection performance.
Mixture-Based Combinatorial Libraries from Small Individual Peptide Libraries: A Case Study on α1-Antitrypsin Deficiency

The design, synthesis and screening of diversity-oriented peptide libraries using a “libraries from libraries” strategy for the development of inhibitors of α1-antitrypsin deficiency are described. The major buttress of the biochemical approach presented here is the use of well-established solid-phase split-and-mix method for the generation of mixture-based libraries. The combinatorial technique iterative deconvolution was employed for library screening. While molecular diversity is the general consideration of combinatorial libraries, exquisite design through systematic screening of small individual libraries is a prerequisite for effective library screening and can avoid potential problems in some cases. This review will also illustrate how large peptide libraries were designed, as well as how a conformation-sensitive assay was developed based on the mechanism of the conformational disease. Finally, the combinatorially selected peptide inhibitor capable of blocking abnormal protein aggregation will be characterized by biophysical, cellular and computational methods.
Handling task dependencies under strided and aliased references

The emergence of multicore processors has increased the need for simple parallel programming models usable by nonexperts. The ability to specify subparts of a bigger data structure is an important trait of High Productivity Programming Languages. Such a concept can also be applied to dependency-aware task-parallel programming models. In those paradigms, tasks may have data dependencies, and those are used for scheduling them in parallel. However, calculating dependencies between subparts of bigger data structures is challenging. Accessed data may be strided, and can fully or partially overlap the accesses of other tasks. Techniques that are too approximate may produce too many extra dependencies and limit parallelism. Techniques that are too precise may be impractical in terms of time and space. We present the abstractions, data structures and algorithms to calculate dependencies between tasks with strided and possibly different memory access patterns. Our technique is performed at run time from a description of the inputs and outputs of each task and is not affected by pointer arithmetic nor reshaping. We demonstrate how it can be applied to increase programming productivity. We also demonstrate that scalability is comparable to other solutions and in some cases higher due to better parallelism extraction.
Running head: Social Media Usage and Sexual Behavior

The major purpose of this study was to assess the relationships among adolescents’ Social media usage, sexual behavior and risk perception. A descriptive survey was employed as a study design. Questionnaire was used to gather data from a random sample of 300 (150 male and 150 female) students of grade 9 through 12 in the selected five private high schools of Bole subcity. Descriptive statistics, Chi-square, t-test, ANOVA and correlations were used to analyze quantitative data. Descriptive statistics revealed that entertainment, communication with people far away and making companionship (34.3%, 20% & 16%) were the major reasons to school adolescents’ social media usage respectively. Weak positive correlation was found between social media usage and sexual behavior [r (298) = . 222, P < . 05]. However, sexual behavior was moderately correlated with the frequency use of social media sites used [r (298) = . 694, P= <0.05]. Descriptive statistics found that the majority (61.3%) of the respondents had high risk perception while 30.7% of the respondents had low risk perception to social media usage. When looking in to the conclusion, adolescents’ sexual behavior in relation to social media usage by default had weak positive correlation. However, their sexual behavior was moderately correlated with the frequency use of social media sites. Hence, among the practical recommendations forwarded, School administrators and teachers should plan and advise school students to use social media sites for educational issues than entertainment, or for companionship. Also, school students should be aware that using social media sites frequently boost to enter sexual behavior. xiii SEXUAL BEHAVIOR Table of
Titan: An Enabling Framework for Activity-Aware "Pervasive Apps" in Opportunistic Personal Area Networks

Upcoming ambient intelligence environments will boast ever larger number of sensor nodes readily available on body, in objects, and in the user's surroundings. We envision "Pervasive Apps", user-centric activity-aware pervasive computing applications. They use available sensors for activity recognition. They are downloadable from application repositories, much like current Apps for mobile phones. A key challenge is to provide Pervasive Apps in open-ended environments where resource availability cannot be predicted. We therefore introduce Titan, a service-oriented framework supporting design, development, deployment, and execution of activity-aware Pervasive Apps. With Titan, mobile devices inquire surrounding nodes about available services. Internet-based application repositories compose applications based on available services as a service graph. The mobile device maps the service graph to Titan Nodes. The execution of the service graph is distributed and can be remapped at run time upon changing resource availability. The framework is geared to streaming data processing and machine learning, which is key for activity recognition. We demonstrate Titan in a pervasive gaming application involving smart dice and a sensorized wristband. We comparatively present the implementation cost and performance and discuss how novel machine learning methodologies may enhance the flexibility of the mapping of service graphs to opportunistically available nodes.
Cooperative quadrocopter ball throwing and catching

This paper presents a method for enabling a fleet of circularly arranged quadrocopters to throw and catch balls with a net. Based on a first-principles model of the net forces, nominal inputs for all involved vehicles are derived for arbitrary target trajectories of the net. Two algorithms that generate open-loop trajectories for throwing and catching a ball are also introduced. A set of throws and catches is demonstrated in the ETH Zurich Flying Machine Arena testbed.
FROM TELE-LABORATORY TO E-LEARNING IN AUTOMATION CURRICULA AT THE UNIVERSITY OF PISA

Abstract The design and development of computational infrastructures supporting existing tele-laboratory experiences in the field of automation and robotics are described. The goal of the activity is to provide a proper e-learning environment in which remote laboratory experiences are integrated in a coherent way. The addition of e-learning features, as self-assessment and progress monitoring tools, asynchronous tutor interaction, authentication, evaluation and follow-up features, has led also to the modification of the original tele-laboratory set-up.
Filling-in Gaps in Textured Images Using Bit-Plane Statistics

In this paper we propose a novel approach for the texture analysis-synthesis problem, with the purpose to restore missing zones in greyscale images. Bit-plane decomposition is used, and a dictionary is build with bit-blocks statistics for each plane. Gaps are reconstructed with a conditional stochastic process, to propagate texture global features into the damaged area, using information stored in the dictionary. Our restoration method is simple, easy and fast, with very good results for a large set of textured images. Results are compared with a state-of-the-art restoration algorithm.
Discovering Novel Fighter Combat Maneuvers in Simulation : Simulating Test Pilot Creativity

This paper reports the authors' ongoing experience with a system for discovering novel fighter combat maneuvers, using a genetics-based machine learning process, and combat simulation. In effect, the genetic learning system in this application is taking the place of a test pilot, in discovering complex maneuvers from experience. The goal of this work is distinct from that of many other studies, in that innovation, and discovery of novelty, is, in itself valuable. This makes the details of aims and techniques somewhat distinct from other genetics-based machine learning research. The paper discusses the details of the application, and the motivations and details of the techniques employed. Results are presented for systems where one player adapts to a fixed strategy opponent, and where two players co-adapt. General implications of this work for other adaptive behavior applications are discussed.
Joint Hα and X-Ray Observations of Massive X-Ray Binaries. I. The B Supergiant System LS I +65 010 = 2S 0114+650

We report on a 3 yr spectroscopic monitoring program of the Hα emission in the massive X-ray binary LS I +65 010 = 2S 0114+650, which consists of a B supergiant and a slowly rotating X-ray pulsar. We present revised orbital elements that yield a period of P = 11.5983 ± 0.0006 days and confirm that the orbit has a nonzero eccentricity e = 0.18 ± 0.05. The Hα emission profile is formed in the base of the wind of the B supergiant primary, and we show how this spectral feature varies on timescales that are probably related to the rotational period of the B supergiant. We also examine the X-ray fluxes from the Rossi X-ray Timing Explorer All-Sky Monitor instrument, and we show that the X-ray orbital light curve has a maximum at periastron and a minimum at the inferior conjunction of the B supergiant. We also show that the wind emission strength and the high-energy X-ray flux appear to vary in tandem on timescales of approximately 1 yr.
The Supernova Legacy Survey 3-year sample: Type Ia supernovae photometric distances and cosmological constraints ,

Aims. We present photometric properties and distance measurements of 252 high redshift Type Ia supernovae (0.15 < z < 1.1) discovered during the first three years of the Supernova Legacy Survey (SNLS). These events were detected and their multi-colour light curves measured using the MegaPrime/MegaCam instrument at the Canada-France-Hawaii Telescope (CFHT), by repeatedly imaging four one-square degree fields in four bands. Follow-up spectroscopy was performed at the VLT, Gemini and Keck telescopes to confirm the nature of the supernovae and to measure their redshifts. Methods. Systematic uncertainties arising from light curve modeling are studied, making use of two techniques to derive the peak magnitude, shape and colour of the supernovae, and taking advantage of a precise calibration of the SNLS fields. Results. A flat ΛCDM cosmological fit to 231 SNLS high redshift type Ia supernovae alone gives Ω_M = 0.211 ± 0.034(stat) ± 0.069(sys). The dominant systematic uncertainty comes from uncertainties in the photometric calibration. Systematic uncertainties from light curve fitters come next with a total contribution of ± 0.026 on Ω_M. No clear evidence is found for a possible evolution of the slope (β) of the colour-luminosity relation with redshift.
A 0.75–6.75 GHz receiver with a digitally controlled LO generator for software-defined radio

This paper describes a receiver composed of a wideband LNA, mixers, and a frequency generator toward multifunction and multistandard mobile terminals. The proposed frequency generator can cover the frequency range from 750 MHz to 6.75 GHz by following the frequency planning which consists of a VCO, two mixers, and four divide-by-2 dividers. Firstly, to achieve better phase noise, a low-phase noise wideband LC VCO is proposed. The power consumption of the VCO is 7.8 mW and its phase noise is −126 dBc/Hz at 1 MHz offset frequency. The LO generator is controlled for the targeted frequency range by turning on and off the mixer and divider input and output buffers. The total power consumption of the LO generator is 27.3~60.6 mW under 1.8 V supply. The phase noise at 1 MHz offset for each frequency band varies from −122 dBc/Hz to −136 dBc/Hz. A 2-stage wideband low noise amplifier has bandwidth of 6.6 GHz (0.2–6.8 GHz), power gain of 13.3 dB including 6 dB loss from buffers, and minimum noise figure of 3.7 dB.
Information Attacks on Online Social Networks

Online social networks have changed the way people interact, allowing them to stay in touch with their acquaintances, reconnect with old friends, and establish new relationships with other people based on hobbies, interests, and friendship circles. Unfortunately, the regrettable concurrence of the users' carefree attitude in sharing information, the often sub-par security measures from the part of the system operators and, eventually, the high value of the published information make online social networks an interesting target for crackers and scammers alike. The information contained can be used to trigger attacks to even more sensible targets and the ultimate goal of sociability shared by the users allows sophisticated forms of social engineering inside the system. This work reviews some typical social attacks that are conducted on social networking systems, carrying real-world examples of such violations and analysing in particular the weakness of password mechanisms. It then presents some solutions that could improve the overall security of the systems.
Performance Analysis of Multiuser Diversity under Transmit Antenna Correlation

In this paper, we investigate the effect of spatial correlation on throughput performance of downlink multi-antenna transmission schemes exploiting multiuser diversity, in which partial channel information such as signal-to-interference plus noise power ratio (SINR) is available at the transmitter. The asymptotic analysis is performed based on the extreme value theory. From this analysis, we demonstrate that the throughput optimal transmission scheme depends on the degree of the antenna correlation and the operating SNR. Especially, the multiuser spatial multiplexing known as the asymptotically optimal transmission scheme is no longer optimal in highly correlated multiple antenna channels.
Gold Terrain Reconstruction from Contours by Skeleton Retraction

Generating terrain models from contour input is still an important process. Most methods have been unsatisfactory, as they either do not preserve the form of minor ridges and valleys, or else they are poor at modeling slopes. A method is described here, based on curve extraction and generalization techniques, that is guaranteed to preserve the topological relationships between curve segments. Based on this approach, which uses the properties of the Voronoi diagram and Delaunay triangulation, it is possible to make reasonable estimates of slopes for terrain models, and to extract meaningful intermediate points for triangulated irregular networks (TINs).
Boolean matching in logic synthesis

A new formulation for finding the existence of a Boolean match between two functions with 'don't cares' is presented. An algorithm for Boolean matching is developed based on this new foundation and is used within a technology mapper as a substitute for tree matching algorithms. The new algorithm is fast and uses symmetries of the gates in the library to speed up the matching process. Local 'don't cares' are computed for each function being mapped in terms of its inputs. To reduce the frequency in which Boolean matching is used, the gates in the library are grouped into classes such that it is sufficient to try to match a function with the class representative. Experimental results show significant improvement in the final area of the mapped circuits. <<ETX>>
A Construction of Biorthogonal Functions to B-Splines with Multiple Knots

Abstract We present a construction of a refinable compactly supported vector of functions which is biorthogonal to the vector of B-splines of a given degree with multiple knots at the integers with prescribed multiplicity. The construction is based on Hermite interpolatory subdivision schemes, and on the relation between B-splines and divided differences. The biorthogonal vector of functions is shown to be refinable, with a mask related to that of the Hermite scheme. For simplicity of presentation the special (scalar) case, corresponding to B-splines with simple knots, is treated separately.