Miracle-dz/UniFAR-FTUs huggingface dataset:
Probing entanglement in adiabatic quantum optimization with trapped ions

Adiabatic quantum optimization has been proposed as a route to solve NP-complete problems, with a possible quantum speedup compared to classical algorithms. However, the precise role of quantum effects, such as entanglement, in these optimization protocols is still unclear. We propose a setup of cold trapped ions that allows one to quantitatively characterize, in a controlled experiment, the interplay of entanglement, decoherence, and non-adiabaticity in adiabatic quantum optimization. We show that, in this way, a broad class of NP-complete problems becomes accessible for quantum simulations, including the knapsack problem, number partitioning, and instances of the max-cut problem. Moreover, a general theoretical study reveals correlations of the success probability with entanglement at the end of the protocol. From exact numerical simulations for small systems and linear ramps, however, we find no substantial correlations with the entanglement during the optimization. For the final state, we derive analytically a universal upper bound for the success probability as a function of entanglement, which can be measured in experiment. The proposed trapped-ion setups and the presented study of entanglement address pertinent questions of adiabatic quantum optimization, which may be of general interest across experimental platforms.
Effect of the Statistical Nature of Fiber Strength on the Predictability of Tensile Properties of Polymer Composites Reinforced with Bamboo Fibers: Comparison of Linear- and Power-Law Weibull Models

In fibrous composites, tensile strength of reinforcements exhibits a stochastic nature, and the mechanical properties of the composites are significantly influenced by such strength variability. The present study aims at providing a comparative investigation of the influence of the statistical variation in fiber strength on the tensile properties of unidirectional composites reinforced by bamboo fibers. Monte-Carlo simulations coupled with the linear- and power-law Weibull distributions are performed to conduct numerical predictions for damage evolution and strength variability of the composites, and the predicted mean strength and failure strain are compared with the experimental results. The Weibull parameters used are achieved through the Maximum Likelihood Estimation with multiple data sets of fiber lengths. Fiber strength statistics is found to have an effect on composite mechanical properties. The results further indicate that the use of the power-law model is relatively efficient for modeling purposes in comparison to the linear-law model, which could be attributed to fiber diameter variation.
A Social and Popularity-Based Tag Recommender

Tag recommendation aims to recommend to a user the most suited tags for a given item. It is an important functionality of resource sharing systems. In this paper we propose a recommendation algorithm, called Fas Tag, that links the relevance of the tags to both their popularity and the opinions of the user's neighbors. Fas Tag assumes that the users are organized in a weighted graph representing, for instance, the similarity or the trust between them. The two salient aspects of Fas Tag are the scoring function it uses to evaluate the relevance of the tags, and its low computation cost. Thus, Fas Tag can make online recommendations, even for large datasets. Moreover, we improve the accuracy of its recommendations by adjusting automatically the size of the recommended list of tags. The experiments we did on several datasets show a significant improvement of the accuracy of the recommendations.
A Human Hepatocyte-Bearing Mouse: An Animal Model to Predict Drug Metabolism and Effectiveness in Humans

Preclinical studies to predict the efficacy and safety of drugs have conventionally been conducted almost exclusively in mice and rats as rodents, despite the differences in drug metabolism between humans and rodents. Furthermore, human (h) viruses such as hepatitis viruses do not infect the rodent liver. A mouse bearing a liver in which the hepatocytes have been largely repopulated with h-hepatocytes would overcome some of these disadvantages. We have established a practical, efficient, and large-scale production system for such mice. Accumulated evidence has demonstrated that these hepatocyte-humanized mice are a useful and reliable animal model, exhibiting h-type responses in a series of in vivo drug processing (adsorption, distribution, metabolism, excretion) experiments and in the infection and propagation of hepatic viruses. In this review, we present the current status of studies on chimeric mice and describe their usefulness in the study of peroxisome proliferator-activated receptors.
SDL and SystemC co-modelling : the protocol SDL models Tester

Testing of data transfer protocol can be performed by means of simulation and a variety of modeling languages may be used for it. Among them there are such languages as SDL and SystemC. Moreover an approach for SDL/SystemC co-modeling has been developed and already applied in practice. This paper discusses applicability of SDL/SystemC co-modeling for testing of data transfer protocols.
Letter by Hamon et al regarding article, "Coronary multidetector computed tomography in the assessment of patients with acute chest pain".

To the Editor: We read with interest the article of Hoffmann et al1 regarding the ability of coronary multidetector computed tomography to rule out acute coronary syndrome in patients presenting to the emergency department with acute chest pain. A note of caution is required in the development of such a strategy. In our opinion, after the use of a single set of biochemical markers for myocardial necrosis exclusion …
Central Bank Independence in a (Very) Non-Neoclassical World

What if it could be possible to convince a completely non-neoclassical economist of the importance of Central Bank independence? The profession currently favors arguments in favor of Central Bank independence that are based on the seminal work by Barro and Gordon (1983 a,b), a model with naturally strong neoclassical assumptions. As a consequence of this, the argument in favor of Central Bank independence routinely given by economists is often not bought by those who question the validity of the neoclassical assumptions. In this paper I argue that Central Bank independence can be beneficial for society even when the economy is entirely non-neoclassical, that is, when workers are all unionized, firms are completely cartelized and inflation arises as the result of distributive struggles among capitalists and workers. This is so because it is the time-inconsistency issue, and not the structure of the economy, that which generates the inflation bias that Central Bank independence is set to eliminate.
A Quantitative Study of the Adoption of Design Patterns by Open Source Software Developers

Copyright © 2005, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. ABSTRACT Several successful projects (Linux, Free-BSD, BIND, Apache, etc.) showed that the collaborative and self-organizing process of developing open source software produces reliable, high quality software. Without doubt, the open source software development process differs in many ways from the traditional development process in a commercial environment. An interesting research question is how these differences influence the adoption of traditional software engineering practices. In this chapter we investigate how design patterns, a widely accepted software engineering practice, are adopted by open source developers for documenting changes. We analyze the development process of almost 1,000 open source software projects using version control information and explore differences in pattern adoption using characteristics of projects and developers. By analyzing these differences, we provide evidence that design patterns are an important practice in open source projects and that there exist significant differences between developers who use design patterns and who do not. Chapter V
Eyelid kinematics for virtual characters

When compared to gaze, animation of the eyelids has been largely overlooked in the computer graphics literature. Eyelid movement plays an important part both in conveying accurate gaze direction and in improving the visual appearance of virtual characters. Eyelids have two major motion components: lid saccades that follow the vertical rotation the eyes, and blinking. Derived from literature in ophthalmology and psychology, this paper presents parametric models for both motion types, and emphasizes their dynamic temporal behaviour. Experimental validation classifies model‐generated animation as similar to that encoded from expensive motion captured data, and significantly exceeding linearly interpolated animation. Copyright © 2010 John Wiley & Sons, Ltd.
Integration of Optimized Modulation Filter Sets Into Deep Neural Networks for Automatic Speech Recognition

Inspired by physiological studies on the human auditory system and by results from psychoacoustics, an amplitude modulation filter bank (AMFB) has been developed and successfully applied to feature extraction for automatic speech recognition (ASR) in earlier work. Here, we address the question as to which amplitude modulation (AM) frequency decomposition leads to optimal ASR performance by proposing a parameterized functional relationship between modulation center frequency and modulation bandwidth. Word error rates (WERs) of ASR experiments with 1551 different AMFBs are systematically evaluated and compared, resulting in the identification of a comparatively narrow range of optimal modulation frequency to modulation bandwidth characteristics. To integrate modulation processing with deep neural network (DNN) acoustic modeling, we propose merging of modulation filter coefficients with DNN weights prior to a final training step and an improved mean-variance normalization scheme for AMFBs. These modifications are shown to result in further reduction of WERs and are indicative of the proposed system's improved generalization ability, when compared across corpora of 100-960 h of data with mismatched training and test conditions. Analysis of DNN-learned temporal AM filtering properties is carried out and implications for the relevance of different modulation regions as well as the relation to psychoacoustic findings are discussed. ASR experiments with the proposed system demonstrate a high degree of robustness against extrinsic acoustic distortions, resulting in, e.g., an average WER of 9.79% on the Aurora-4 task.
Reply to Binmore: Social Norms or Social Preferences?

I am in agreement with many of Ken Binmore’s remarks in Social Norms and Social Preferences (2010). Like Binmore, I welcome the breath of fresh air that behavioral economics has brought to economic theory, and along with Binmore, the themes of justice and reciprocity are particularly important for my interest in the evolution of social norms. Binmore is correct is asserting that neoclassical economics doesnot dependon the viewthat peopleare selfish,and as he pointsout, in market contexts, laboratory experiments indicate that traditional theory works well. Behavioral economic findings are thus enriching and expanding neoclassical economics rather than undermining it. Also like Binmore, I believe social norms are an emergent property of human sociality, and exist as macrosocial structures that are not reducible to the preferences of individuals. As Binmore stresses, it is difficult to formulate a coherent theory of social preferences unless one has a systemic model of social norms existing outside of the system of individual preferences. Indeed, in Gintis (2009) I identify the endeavor to subsume social norms under the rubric of social preferences as an untenable form of methodological individualism. Given this basic agreement on the most, if not all, scientific points, this note hopes to aid the reader in understanding and evaluating the nature of our disagreements. Ken Binmore imputes a lack of personal character and professional integrity to those with whom he disagrees. The objects of his critique “muscle in on neighboring disciplines,” with a “new imperial venture,” they “downplay inconvenient facts,” and they have “betrayed the scientific ethos. ” Such assertions threaten to turn a useful dialog into unenlightened name-calling. Binmore claims that Experiments on the one-shot Prisoners Dilemma show that subjects (usually students) who are new to the game contribute slightly more than 50% of the time, but that their behavior changes as they gain experience. After playing repeatedly (against a new opponent each time), about 90% of subjects end up free riding after ten trials
RELATIONAL DATABASE DESIGN FOR THE TEST OF THE KSTAR SUPERCONDUCTING MAGNET SYSTEM

The Korea Superconducting Tokamak Advanced Research (KSTAR) superconducting magnet system consists of 16 TF (Toroidal Field) and 14 PF (Poloidal Field) coils. Both of TF and PF coils use internally-cooled conductors. In order to validate the design of the KSTAR TF coil, a full-scale prototype TF coil, TF00, is developed. For the test of TF00, a large scale superconducting magnet and conductor test facility, SSTF (Samsung Superconductor Test Facility), has been constructed. The data acquisition and control system for SSTF is based on Linux system and Experimental Physics and Industrial Control System (EPICS) is used for the acquisition and distribution of experimental data. A relational database management system is used for the configuration of the EPICS record data. Calculation routines, which convert a measured voltage to a physical value, are added to the EPICS IOC (Input-Output Controller) application, which is ported to an i386 PC with the Real-Time Executive for Multiprocessor Systems (RTEMS).
Online Covering with Convex Objectives and Applications

We give an algorithmic framework for minimizing general convex objectives (that are differentiable and monotone non-decreasing) over a set of covering constraints that arrive online. This substantially extends previous work on online covering for linear objectives (Alon {\em et al.}, STOC 2003) and online covering with offline packing constraints (Azar {\em et al.}, SODA 2013). To the best of our knowledge, this is the first result in online optimization for generic non-linear objectives; special cases of such objectives have previously been considered, particularly for energy minimization. As a specific problem in this genre, we consider the unrelated machine scheduling problem with startup costs and arbitrary $\ell_p$ norms on machine loads (including the surprisingly non-trivial $\ell_1$ norm representing total machine load). This problem was studied earlier for the makespan norm in both the offline (Khuller~{\em et al.}, SODA 2010; Li and Khuller, SODA 2011) and online settings (Azar {\em et al.}, SODA 2013). We adapt the two-phase approach of obtaining a fractional solution and then rounding it online (used successfully to many linear objectives) to the non-linear objective. The fractional algorithm uses ideas from our general framework that we described above (but does not fit the framework exactly because of non-positive entries in the constraint matrix). The rounding algorithm uses ideas from offline rounding of LPs with non-linear objectives (Azar and Epstein, STOC 2005; Kumar {\em et al.}, FOCS 2005). Our competitive ratio is tight up to a logarithmic factor. Finally, for the important special case of total load ($\ell_1$ norm), we give a different rounding algorithm that obtains a better competitive ratio than the generic rounding algorithm for $\ell_p$ norms. We show that this competitive ratio is asymptotically tight.
Okapi at TREC-4

The BSS, which has been used in all City's TREC experiments, is a set-oriented ranked output system designed primarily for probabilistic{type retrieval of textual material using inverted indexes. There is a family of built-in weighting functions as described in [1, Section 3]. In addition to weighting and ranking facilities it has the usual boolean and quasi-boolean (positional) operations. There are a number of non-standard set operations, some of which were added during the TREC{4 experiments.
Comparing the Acute Effects of Antidepressants on Serotonin in vivo

Depression, a debilitating mood disorder, affects 12% of the American population [1]. Chemical imbalances in the serotonergic system are strongly implicated in the development and treatment of depression. However, the precise neurochemical mechanisms remain unknown. This is primarily due to the lack of analytical techniques that can measure serotonin in the brain with high sensitivity at a physiologically relevant temporal resolution. There is a critical need to understand serotonin actions as contemporary antidepressants commonly target serotonin re-uptake in the brain. Moreover, efficacy is variable, typically requiring a chronic treatment period of 2-4 weeks thus limiting its utility as an acute therapy.
RSU based efficient vehicle authentication mechanism for VANETs

Security and privacy are the two major concerns in VANETs. Due to highly dynamic environment in VANETs computation time for authentication is more. At the same time most of the privacy preserving schemes is prone to Sybil attacks. In this paper we propose a lightweight authentication scheme between vehicle to RSU, vehicle to vehicles and to build a secure communication system. In this method we make use of timestamps approach and also reduce the computation cost for authentication in highly dense traffic zones. The privacy of the vehicle is preserved by not disclosing its real identity.
The Effect of Industrial Food Processing on Potentially Health-Beneficial Tomato Antioxidants

Increasing desires from both consumers and producers to understand better which nutritive components are present in our food and how these are influenced by industrial processing strategies is resulting in extra research involving the use of state-of-the-art technologies to generate novel biochemical information. In this review, attention has been focused on tomato as this is a product eaten right across the world both as fresh produce and after having been processed in a wide variety of ways. There is a particular interest in tomato as it is a major component in the so-called “Mediterranean diet” which has recently been associated with a healthier lifestyle. Tomatoes are rich sources of a variety of nutritional compounds and especially some key antioxidant components such as the carotenoid lycopene, vitamin C, and a range of polyphenols. The potentially protective properties of these antioxidants are of great interest and the consumer has already become aware of their potential importance. Surveying the literature has revealed that much research has been done on the biochemical composition of tomato and its products. However, it remains difficult to make clear conclusions on optimizing the processing strategy. Many, apparently conflicting, findings have been reported and consequently, in this review, we have drawn attention to these and have attempted to clarify their cause. Finally, a range of recommendations has been made as to how future research might be performed in order to generate more concrete conclusions enabling recommendations towards more optimized processing strategies.
Optimal quantized lifting coefficients for the 9/7 wavelet [image compression applications]

The lifting structure has been shown to be computationally efficient for implementing filter banks. The hardware implementation of a filter bank requires that the lifting coefficients be quantized. The quantization method determines compression performance, hardware size, hardware speed and energy. We investigate the implementation of two lifting coefficient sets, rational and irrational, for the biorthogonal 9/7 wavelet. Six different approaches are used to find optimal quantized lifting coefficients from these sets. We find that the best hardware and PSNR performance is obtained using the rational coefficient set quantized with gain compensation and lumped scaling.
Predicting disease by using data mining based on healthcare information system

This paper applies the data mining process to predict hypertension from patient medical records with eight other diseases. A sample with the size of 9862 cases has been studied. The sample was extracted from a real world Healthcare Information System database containing 309383 medical records. We observed that the distribution of patient diseases in the medical database is imbalanced. Under-sampling technique has been applied to generate training data sets, and data mining tool Weka has been used to generate the NaIve Bayesian and J-48 classifiers. In addition, an ensemble of five J-48 classifiers was created trying to improve the prediction performance, and rough set tools were used to reduce the ensemble based on the idea of second-order approximation. Experimental results showed a little improvement of the ensemble approach over pure Na'ive Bayesian and J-48 in accuracy, sensitivity, and F-measure.
MT-Aided Analysis of Comprehension of English Verb Preposition Constructions

The paper presents a new method for analysis of natural language comprehension. In this paper, we narrow the analysis down to English verb preposition constructions, as they are very complicated not only in the composition but also in the meaning. Although we can make human or statistics investigation to study the comprehension of verb preposition constructions, human's incomplete memories and the irrelevance between human's comprehension and statistics survey cannot keep this problem into perspective. However, an MT system can both provide almost infinite memories and simulate a certain human comprehension. In this paper, by virtue of our E-C MT system and NIST evaluation metric, we want to know to what extent verb preposition constructions could trouble the comprehension process and which kind of the constructions could pose the biggest headache for learners. Having evaluated the scored translation results from our system by removing our system's rules with respect to all kinds of verb preposition constructions, we could figure out the difficult points of understanding different verb preposition constructions for English-learners.
Bridging the divide between software developers and operators using logs

There is a growing gap between the software development and operation worlds. Software developers rarely divulge development knowledge about the software to operators, while operators rarely communicate field knowledge to developers. To improve the quality and reduce the operational cost of large-scale software systems, bridging the gap between these two worlds is essential. This thesis proposes the use of logs as mechanism to bridge the gap between these two worlds. Logs are messages generated from statements inserted by developers in the source code and are often used by operators for monitoring the field operation of a system. However, the rich knowledge in logs has not yet been fully used because of their non-structured nature, their large scale, and the use of the ad hoc log analysis techniques. Through case studies on large commercial and open source systems, we plan to demonstrate the value of logs as a tool to support developers and operators.