Miracle-dz/UniFAR-FTUs huggingface dataset:
High-fidelity controlled-σ Z gate for resonator-based superconducting quantum computers

A possible building block for a scalable quantum computer has recently been demonstrated [M. Mariantoni et al., Science 334, 61 (2011)]. This architecture consists of superconducting qubits capacitively coupled both to individual memory resonators as well as a common bus. In this work we study a natural primitive entangling gate for this and related resonator-based architectures, which consists of a CZ operation between a qubit and the bus. The CZ gate is implemented with the aid of the non-computational qubit |2> state [F. W. Strauch et al., Phys. Rev. Lett. 91, 167005 (2003)]. Assuming phase or transmon qubits with 300 MHz anharmonicity, we show that by using only low frequency qubit-bias control it is possible to implement the qubit-bus CZ gate with 99.9% (99.99%) fidelity in about 17ns (23ns) with a realistic two-parameter pulse profile, plus two auxiliary z rotations. The fidelity measure we refer to here is a state-averaged intrinsic process fidelity, which does not include any effects of noise or decoherence. These results apply to a multi-qubit device that includes strongly coupled memory resonators. We investigate the performance of the qubit-bus CZ gate as a function of qubit anharmonicity, indentify the dominant intrinsic error mechanism and derive an associated fidelity estimator, quantify the pulse shape sensitivity and precision requirements, simulate qubit-qubit CZ gates that are mediated by the bus resonator, and also attempt a global optimization of system parameters including resonator frequencies and couplings. Our results are relevant for a wide range of superconducting hardware designs that incorporate resonators and suggest that it should be possible to demonstrate a 99.9% CZ gate with existing transmon qubits, which would constitute an important step towards the development of an error-corrected superconducting quantum computer.
A survey on issues in non-functional requirements elicitation

One of the primary responsibilities of requirement engineer is the elicitation of non-functional and functional requirements. Functional requirements sketch out the functionality, the system has to be performed while non-functional requirements compel the restrictions on this functionality. Software industry is raising its demand for not only the required functionality but the necessity of non-functional requirements too such as performance, security, usability, security, privacy etc. The current practice in the industry is to deal with functional requirements as first class requirements while non-functional requirements are only catered at design and implementation level. This approach leaves a serious flaw in the system design towards user satisfaction and often results in the failure of projects such as the classic example of London Ambulance System[1]. The chances of software success can be maximized when dealing with NFR at the requirements level. This literature survey is a first effort of its kind to seek key NFR challenges and issues while elicitation level of requirement engineering. It also find-outs the approaches and methods that are suggested in literature to deal with these issues.
A background recovery based matting approach

Alpha matting aims at extracting foreground object accurately from an image. In alpha matting, all pixels are considered as the composition of its foreground and background color by an opacity value (alpha). Alpha matting is an extremely challenging task for its ill-posed nature. Some existing techniques aim at finding the best foreground/background color pair to every pixel by sampling nearby pixels. Some others rely on color propagation like solving matting affinity matrix. In this paper, we propose a novel method combined the advantages of both sampling and propagation based approaches to get high quality matte. First, we propagate the information of background to unknown region using inpainting technique. Then, we use a novel sampling method to get the estimation of foreground color. Finally, we solve a cost function that minimizes the color distortion combined with alpha matte smoothness error. Experimental results show that high quality matte can be obtained using our method.
Carmen: A software tool for probabilistic graphical models

Carmen is a software tool, currently under development, for probabilistic graphical models. The intention of making it useful for diﬀerent research groups and also reliable for building real-world applications implies that the system must be robust, eﬃcient, scalable, and extensible. For this reason, we have tried to closely adhere to the principles of software engineering, with special emphasis on documenting the source code. This paper describes the main features of Carmen and the results of a preliminary rough analysis of its performance.
Artificial Intelligence through the eyes of Organised Sound

Artificial intelligence is a rich and still-developing field with many musical applications. This article surveys the use of artificial intelligence approaches in the pages of Organised Sound, from the first issue to the present day. Often, these approaches are designed with note-based composition in mind, but the research we present finds that artificial intelligence has also had a significant impact in electroacoustic music such as sound analysis and organisation, real-time compostion, and interactive performance-driven composition. Two distinct categories emerge in the literature; philosophically inspired, symbolic approaches, and biologically inspired artificial life approaches, though the two are not mutually exclusive in their use, and in some cases are combined to achieve ‘best of both’ solutions. That said, as Organised Sound is uniquely positioned in the electroacoustic music community it is somewhat surprising that work tackling issues of form and structure, which artificial intelligence can be readily adaptable to, is not more present in these pages. We consider this as well as further hybrid models, as likely avenues for future work.
Indexing and querying linguistic metadata and document content

The need for efficient corpus indexing and querying arises frequently both in machine learning-based and human-engineered natural language processing systems. This paper presents the ANNIC system, which can index documents not only by content, but also by their linguististic annotations and features. It also enables users to formulate versatile queries mixing keywords and linguistic information. The result consists of the matching texts in the corpus, displayed within the context of linguistic annotations (not just text, as is customary for KWIC systems). The data is displayed in a graphical user interface, which facilitates its exploration and the discovery of new patterns, which can in turn be tested by launching new
Valuing the Unique: The Economics of Singularities

In this landmark work of economic sociology, Lucien Karpik introduces the theory and practical tools needed to analyze markets for singularities. Singularities are goods and services that cannot be studied by standard methods because they are multidimensional, incommensurable, and of uncertain quality. Examples include movies, novels, music, artwork, fine wine, lawyers, and doctors. Valuing the Unique provides a theoretical framework to explain this important class of products and markets that for so long have eluded neoclassical economics. With this innovative theory--called the economics of singularities--Karpik shows that, because of the uncertainty and the highly subjective valuation of singularities, these markets are necessarily equipped with what he calls "judgment devices"--such as labels, brands, guides, critics, and rankings--which provide consumers with the credible knowledge needed to make reasonable choices. He explains why these markets are characterized by the primacy of competition by qualities over competition by prices, and he identifies the conditions under which singularities are constructed or are in danger of losing their uniqueness. After demonstrating how combinations of the numerous and multiform judgment devices can be used to identify different market models, Karpik applies his analytical tools to the functioning of a large number of actual markets, including fine wines, movies, luxury goods, pop music, and legal services.
Iterative video-aware waterfilling algorithm for SVC streaming over OFDMA downlink channel

This paper introduced VWF for streaming SVC-streams over OFDMA downlink channel. In order to minimize average video distortion, VWF iteratively obtains user weights by considering RD properties of SVC-streams. It is discussed that minimization of average video distortion also provides fairness among users in terms of video distortion. VWF improves average PSNR over PWF by 2dB, maintaining fairness (in terms of standard deviation of MSE) not inferior to PWF which is designed to provide proportional fairness.
User interface for integrating airport operations

In the past few decades, air traffic problems at major airports have been increased significantly and are expected over in the near future, which imposes a high requirement for more efficient cooperation across all airport operations. Thus, determining efficient airport operations is an important and critical problem for airports, airlines, passengers and other stakeholders. In this situation, the complexity of the problem means that advanced decision support systems are needed to guarantee efficient airside airport operations and to mitigate the environmental impact. The research Integrating and Automating Airport Operations has the main driver to decrease any detrimental effects of airport operations upon the environment. It represents a wide ranging multi-disciplinary and cross-institutional initiative to exploit recent research advances in automated search methodologies and decision support techniques for air operations (and other related areas). This research will build integrated computational models. As a part of the research, developing Human Machine Interface (HMI) is based on the user interface requirements making a platform to link the air operation models together, to build a computer simulation of the airport problem solving environment. The research is funded by EPSRC and focuses on the Manchester Airport.
On the Energy-Spectral Efficiency Trade-off of the MRC Receiver in Massive MIMO Systems with Transceiver Power Consumption

We consider the uplink of a multiuser massive MIMO system wherein a base station (BS) having $M$ antennas communicates coherently with $K$ single antenna user terminals (UTs). We study the energy efficiency of this system while taking the transceiver power consumption at the UTs and the BS into consideration. For a given spectral efficiency $R$ and fixed transceiver power consumption parameters, we propose and analyze the problem of maximizing the energy efficiency as a function of $(M,K)$. For the maximum ratio combining (MRC) detector at the BS we show that with increasing $R$, $(M,K)$ can be adaptively increased in such a way that the energy efficiency converges to a positive constant as $R \rightarrow \infty$ ($(M,K)$ is increased in such a way that a constant per-user spectral efficiency $R/K$ is maintained). This is in contrast to the fixed $(M,K)$ scenario where the energy efficiency is known to converge to zero as $R \rightarrow \infty$. We also observe that for large $R$, the optimal $(M,K)$ maximizing the energy efficiency is such that, the total power consumed by the power amplifiers (PA) in all the $K$ UTs is a small fraction of the total system power consumption.
TrTok: A Fast and Trainable Tokenizer for Natural Languages

TrTok: A Fast and Trainable Tokenizer for Natural Languages We present a universal data-driven tool for segmenting and tokenizing text. The presented tokenizer lets the user define where token and sentence boundaries should be considered. These instances are then judged by a classifier which is trained from provided tokenized data. The features passed to the classifier are also defined by the user making, e.g., the inclusion of abbreviation lists trivial. This level of customizability makes the tokenizer a versatile tool which we show is capable of sentence detection in English text as well as word segmentation in Chinese text. In the case of English sentence detection, the system outperforms previous methods. The software is available as an open-source project on GitHub1.
Waiting for Mariang Makiling: Essays in Philippine Cultural History

Waiting for Mariang Makiling is an engaging exploration of Philippine cultural history. It is striking for the diversity of texts it takes up: the legend of a mountain goddess, Pigafetta's discovery account of the Philippines, the life of a seventeenth-century Christian convert, the foundation narrative of a Marian shrine, colonial books of conduct, memoirs of Filipino intellectuals, a Bisayan love poem, political talk on radio, a dinner in nineteenth-century Cebu. A singleness of purpose guides the reader through a forest of texts toward an appreciation of the larger issues of cultural politics and nation formation.
Labour protection and informal work: A cross‐national analysis of European countries, 2004–2012

Informal work, defined as work performed without a formal contract, lowers productivity, reduces tax revenue and hampers economic growth. Reducing informal work is a policy objective in developed and developing countries alike. Yet, particularly since the onset of the global financial crisis in 2008, most socio-economic policy reforms across Europe have reduced the generosity of unemployment benefit schemes and deregulated employment protection. The authors argue that, while such reforms may have contributed to reducing unemployment, they might also have increased the incidence of informal work. Using European Social Survey data for 2004–12, they find that labour protection is effective in reducing informal wage employment.
Evolutionary multiobjective design of a flexible caudal fin for robotic fish

Robotic fish accomplish swimming by deforming their bodies or other fin-like appendages. As an emerging class of embedded computing system, robotic fish are anticipated to play an important role in environmental monitoring, inspection of underwater structures, tracking of hazardous wastes and oil spills, and the study of live fish behaviors. While integration of flexible materials (into the fins and/or body) holds the promise of improved swimming performance (in terms of both speed and maneuverability) for these robots, such components also introduce significant design challenges due to the complex material mechanics and hydrodynamic interactions. The problem is further exacerbated by the need for the robots to meet multiple objectives (e.g., both speed and energy efficiency). In this paper, we propose an evolutionary multiobjective optimization approach to the design and control of a robotic fish with a flexible caudal fin. Specifically, we use the NSGA-II algorithm to investigate morphological and control parameter values that optimize swimming speed and power usage. Several evolved fin designs are validated experimentally with a small robotic fish, where fins of different stiffness values and sizes are printed with a multi-material 3D printer. Experimental results confirm the effectiveness of the proposed design approach in balancing the two competing objectives.
Down-regulated in Human Hepatocellular Carcinoma Cyclin G 1 Is a Target of miR-122 a , a MicroRNA Frequently

We investigated the role of microRNAs (miRNAs) in the pathogenesis of human hepatocellular carcinoma (HCC). A genome-wide miRNA microarray was used to identify differentially expressed miRNAs in HCCs arisen on cirrhotic livers. Thirty-five miRNAs were identified. Several of these miRNAs were previously found deregulated in other human cancers, such as members of the let-7 family, mir-221, and mir-145 . In addition, the hepato-specific miR-122a was found downregulated in f70% of HCCs and in all HCC-derived cell lines. Microarray data for let-7a, mir-221, and mir-122a were validated by Northern blot and real-time PCR analysis. Understanding the contribution of deregulated miRNAs to cancer requires the identification of gene targets. Here, we show that miR-122a can modulate cyclin G1 expression in HCC-derived cell lines and an inverse correlation between miR-122a and cyclin G1 expression exists in primary liver carcinomas. These results indicate that cyclin G1 is a target of miR-122a and expand our knowledge of the molecular alterations involved in HCC pathogenesis and of the role of miRNAs in human cancer. [Cancer Res 2007;67(13):6092–9]
A pitch-synchronous speech analysis and synthesis method for DNN-SPSS system

This paper proposes a pitch-synchronous deep neural network (DNN)-based statistical parametric speech synthesis (SPSS) system. The pitch-synchronous frames defined by the locations of glottal closure instants (GCIs) are used to extract speech parameters, which significantly reduce coupling effects between vocal tract and excitation signals. As a result, the distribution of spectral parameters within the same context of phonetic classes becomes more uniform, which improves a model trainability especially for a small-scaled DNN framework. Although the effectiveness of pitch-synchronous approach has been proven in other applications, it is not trivial to integrate the method into the typical DNN-based SPSS systems that have regularized structures, i.e. fixed frame rate and fixed dimension of features. In this paper, we design a new DNN-based SPSS system that pitch-synchronously trains and generates speech parameters. Objective and subjective test results verify the superiority of the proposed system compared to the conventional approach.
A Temporal Perspective on the Interplay of Demography and Selection on Deleterious Variation in Humans

When mutations have small effects on fitness, population size plays an important role in determining the amount and nature of deleterious genetic variation. The extent to which recent population size changes have impacted deleterious variation in humans has been a question of considerable interest and debate. An emerging consensus is that the Out-of-Africa bottleneck and subsequent growth events have been too short to cause meaningful differences in genetic load between populations; though changes in the number and average frequencies of deleterious variants have taken place. To provide more support for this view and to offer additional insight into the divergent evolution of deleterious variation across populations, we numerically solve time-inhomogeneous diffusion equations and study the temporal dynamics of the frequency spectra in models of population size change for modern humans. We observe how the response to demographic change differs by the strength of selection, and we then assess whether similar patterns are observed in exome sequence data from 33,370 and 5203 individuals of non-Finnish European and West African ancestry, respectively. Our theoretical results highlight how even simple summaries of the frequency spectrum can have complex responses to demographic change. These results support the finding that some apparent discrepancies between previous results have been driven by the behaviors of the precise summaries of deleterious variation. Further, our empirical results make clear the difficulty of inferring slight differences in frequency spectra using recent next-generation sequence data.
On the Turkish Controllee

In this paper we claim that Turkish controls the syntactic subject, like English, Icelandic, Dyirbal and German, although not all languages control the syntactic subject, e.g. Basque, Inuit and Tagalog, which control the maximally LF-commanding argument (which we shall call the semantic subject, following Bozsahin and Steedman (in submission)). At least in some of these languages, the semantic subject and the syntactic subject are not the same argument. Hence control cross-cuts accusativity/ergativity. The claim for Turkish might seem obvious but we think it requires justification in the face of facts from other languages: Although it is common to assume that control requires a VP complement therefore what is “missing” from the controlled clause is the syntactic subject, what appears to be controlled in some ergative languages is the syntactic subject, but not all. Majority of ergative languages control the ergative argument, which can be shown in many of them not to be the syntactic subject. Moreover, although accusative languages by and large conflate syntactic subjecthood and semantic subjecthood in their surface grammar, thereby allowing a (local) semantic relation like control to be read off from syntactic structure or argument structure without confusion, not all of them do. For example, Zaenen (1993) claims that control of unaccusatives in Dutch is not felicitous if not ungrammatical, unlike English, e.g. the window tries to open, but Dutch makes no case distinction in the single argument of unergatives, the single argument of unaccusatives and the primary argument of transitives (i.e. the syntactic subject), and unergatives can be controlled. Hence the choices for the controllee must be examined for each language.1 We do this for Turkish in this paper. First we look at control as a lexical property (§2). Then we consider accusativity and ergativity, i.e. ways of organising grammatical relations, and their effect on control (§3). We attempt to identify the Turkish controllee in §4, before concluding in §5.
Hawking Effect in 2-D String Theory

We use the matrix model to study the final state resulting from a coherent high energy pulse in 2-d string theory at large string coupling. We show that the outgoing signal produced via reflection off the potential has a thermal spectrum, with the correct temperature and profile to be identified with Hawking radiation. We confirm its origin as geometrical radiation produced by the gravitational background. However, for a total incoming energy M, the amount of energy carried by the thermal radiation scales only as log(M). Most of the incoming energy is returned via the transmitted wave, which does not have a thermal spectrum, indicating the absence of macroscopic black hole formation.
Neural Dynamics of Choice: Single-Trial Analysis of Decision-Related Activity in Parietal Cortex

Previous neurophysiological studies of perceptual decision-making have focused on single-unit activity, providing insufficient information about how individual decisions are accomplished. For the first time, we recorded simultaneously from multiple decision-related neurons in parietal cortex of monkeys performing a perceptual decision task and used these recordings to analyze the neural dynamics during single trials. We demonstrate that decision-related lateral intraparietal area neurons typically undergo gradual changes in firing rate during individual decisions, as predicted by mechanisms based on continuous integration of sensory evidence. Furthermore, we identify individual decisions that can be described as a change of mind: the decision circuitry was transiently in a state associated with a different choice before transitioning into a state associated with the final choice. These changes of mind reflected in monkey neural activity share similarities with previously reported changes of mind reflected in human behavior.