Miracle-dz/UniFAR-FTUs huggingface dataset:
Under review as a conference paper at ICLR 2017 D ISCOVERING OBJECTS AND THEIR RELATIONS FROM ENTANGLED SCENE REPRESENTATIONS

Our world can be succinctly and compactly described as structured scenes of objects and relations. A typical room, for example, contains salient objects such as tables, chairs and books, and these objects typically relate to each other by virtue of their correlated features, such as position, function and shape. Humans exploit knowledge of objects and their relations for learning a wide spectrum of tasks, and more generally when learning the structure underlying observed data. In this work, we introduce relation networks (RNs) a general purpose neural network architecture for object-relation reasoning. We show that RNs are capable of learning object relations from scene description data. Furthermore, we show that RNs can act as a bottleneck that induces the factorization of objects from entangled scene description inputs, and from distributed deep representations of scene images provided by a variational autoencoder. The model can also be used in conjunction with differentiable memory mechanisms for implicit relation discovery in one-shot learning tasks. Our results suggest that relation networks are a powerful architecture for solving a variety of problems that require object relation reasoning.
Avoiding coincidental correctness in boundary value analysis

In partition analysis we divide the input domain to form subdomains on which the system's behaviour should be uniform. Boundary value analysis produces test inputs near each subdomain's boundaries to find failures caused by incorrect implementation of the boundaries. However, boundary value analysis can be adversely affected by coincidental correctness---the system produces the expected output, but for the wrong reason. This article shows how boundary value analysis can be adapted in order to reduce the likelihood of coincidental correctness. The main contribution is to cases of automated test data generation in which we cannot rely on the expertise of a tester.
Form and Content in Computer Science (1970 ACM turing lecture)

The trouble with computer science today is an obsessive concern with form instead of content. No, that is the wrong way to begin. By any previous standard the vitality of computer science is enormous; what other intellectual area ever advanced so far in twenty years? Besides, the theory of computation perhaps encloses, in some way, the science of form, so that the concern is not so badly misplaced. Still, I will argue that an excessive preoccupation with formalism is impeding our development. Before entering the discussion proper, I want to record the satisfaction my colleagues, students, and I derive from this Turing award. The cluster of questions, once philosophical but now scientific, surrounding the understanding of intelligence was of paramount concern to Alan Turing, and he along with a few other thinkers--notably Warren S. McCulloch and his young associate, Walter P i t t s made many of the early analyses tha t led both to the computer itself and to the new technology of artificial intelligence. In recognizing this area, this award should focus attention on other work of my own scientific family--especially Ray Solomonoff, Oliver Selfridge, John McCarthy, Allen Newell, Herbert Simon, and Seymour Papert, my closest associates in a decade of work. Papert 's views pervade this essay. This essay has three parts, suggesting form-content confusion in theory of computation, in programming languages, and in education.
Minimal and Complete Prefix Unification for Non-Classical Theorem Proving

For theorem proving in non-classical logics two similar ap- proaches have been established: a matrix characterization of Wallen and Ohlbach's resolution calculus. In both cases the essential extension of the classical calculi is a need for unifying the so-called prefixes of atomic formulae or so-called world-paths respectively. We present a specialized string-unification algorithm which computes a minimal set of most general unifiers. By transforming systems of equa- tions we obtain an elegant and ecient procedure which applies to in- tuitionistic logic and the modal logic S4. With some modifications it also applies to the modal logics D, K, D4, K4, S5, and T. We explain our method by an intuitive graphical illustration, prove termination, correct- ness, completeness, and minimality, and investigate its complexity.
Compositional ideas in the bayesian analysis of categorical data with application to dose finding clinical trials

Compositional random vectors are fundamental tools in the Bayesian analysis of categorical data.Many of the issues that are discussed with reference to the statistical analysis of compositionaldata have a natural counterpart in the construction of a Bayesian statistical model for categoricaldata.This note builds on the idea of cross-fertilization of the two areas recommended by Aitchison (1986)in his seminal book on compositional data. Particular emphasis is put on the problem of whatparameterization to use
Template-Directed Ligation of Tethered Mononucleotides by T4 DNA Ligase for Kinase Ribozyme Selection

Background In vitro selection of kinase ribozymes for small molecule metabolites, such as free nucleosides, will require partition systems that discriminate active from inactive RNA species. While nucleic acid catalysis of phosphoryl transfer is well established for phosphorylation of 5′ or 2′ OH of oligonucleotide substrates, phosphorylation of diffusible small molecules has not been demonstrated. Methodology/Principal Findings This study demonstrates the ability of T4 DNA ligase to capture RNA strands in which a tethered monodeoxynucleoside has acquired a 5′ phosphate. The ligation reaction therefore mimics the partition step of a selection for nucleoside kinase (deoxy)ribozymes. Ligation with tethered substrates was considerably slower than with nicked, fully duplex DNA, even though the deoxynucleotides at the ligation junction were Watson-Crick base paired in the tethered substrate. Ligation increased markedly when the bridging template strand contained unpaired spacer nucleotides across from the flexible tether, according to the trends: A2>A1>A3>A4>A0>A6>A8>A10 and T2>T3>T4>T6≈T1>T8>T10. Bridging T's generally gave higher yield of ligated product than bridging A's. ATP concentrations above 33 µM accumulated adenylated intermediate and decreased yields of the gap-sealed product, likely due to re-adenylation of dissociated enzyme. Under optimized conditions, T4 DNA ligase efficiently (>90%) joined a correctly paired, or T∶G wobble-paired, substrate on the 3′ side of the ligation junction while discriminating approximately 100-fold against most mispaired substrates. Tethered dC and dG gave the highest ligation rates and yields, followed by tethered deoxyinosine (dI) and dT, with the slowest reactions for tethered dA. The same kinetic trends were observed in ligase-mediated capture in complex reaction mixtures with multiple substrates. The “universal” analog 5-nitroindole (dNI) did not support ligation when used as the tethered nucleotide. Conclusions/Significance Our results reveal a novel activity for T4 DNA ligase (template-directed ligation of a tethered mononucleotide) and establish this partition scheme as being suitable for the selection of ribozymes that phosphorylate mononucleoside substrates.
Optimizing the parameters of tilting surfaces in robotic workcells

Pick-and-place regrasp is an important grasp and manipulation skill for a robot to rearrange the world around it. This paper discusses how to design a tilted work surface for robotic workcells so that the robot inside the cell can improve its pick-and-place regrasps. In particular, the workcell design is guided by two heuristics, which simultaneously increase the number of stable placements of the objects to be grasped and the gripper's manipulability. We leverage regression techniques to compute a continuous function for fitting the multiplication of these two heuristics, and then maximize the fitted function for optimizing the parameters of tilted surfaces in a workcell. Experiments on using tilted surfaces to improve the stability and manipulability of various objects validate our approach.
Contribution of atmospheric processes affecting the dynamics of air pollution in South-Western Europe during a typical summertime photochemical episode

Abstract. The southern Mediterranean region frequently experiences critical levels of photochemical pollutants during summertime. In order to account for the contribution of different atmospheric processes during this type of episodes, the WRF-ARW/HERMES/CMAQ modelling system was applied with high resolution (1 km2, 33 sigma vertical layers, 1 h) to assess the different dynamics in a coastal environment and an inland-continental zone: the North-Eastern and Central Iberian Peninsula (NEIP and CIP, respectively). The former is characterized by a very complex terrain, while the latter behaves as a flat area, which clearly affects the pattern of local flows. A representative type of photochemical pollution episode (occurring over 78% of summer days) which occurred during 17–18 June, 2004 is selected as the study period. The CMAQ Integrated Process Rate provides the hourly contributions of atmospheric processes to net O3, NOx and NMVOCs concentrations. The O3 photochemical formation occurs mainly in downwind areas from the main NOx emission sources during midday. At surface level it accounts for 50 to 75 μg m−3 h−1. The urban areas and main roads, as main sources of NOx emissions, act as O3 sinks, quenching up to −200 μg m−3 per hour during the traffic circulation peaks. The O3 concentration gradient generated, larger during daytime, increases the contribution of diffusion processes to ground-level O3 (up to 200 μg m−3 h−1 fluxes, mainly from upper vertical layers). The maximum positive contributions of gas-phase chemistry to O3 occur in the coastal domain at high levels (around 500 to 1500 m a.g.l.), while in the continental domain they take place in the whole atmospheric column under the PBL. The transport of ozone precursors by advective flows determines the location of the maximum O3 surface concentrations. The O3 chemical formation involves the oxidation of less NMVOCs in the NEIP than in the CIP domains, due to differences in chemical sensitivity between these areas. The dry deposition is an important sink in the lowest layer of the model, together with vertical diffusion flows. Finally, the contributions from cloud processes, wet deposition and heterogeneous chemistry are negligible during the whole episode, characterized by a high solar radiation and neither precipitation nor cloudiness. This process analysis provides new quantitative information about the origin of the peaks of O3 and its precursors, aiding the design of abatement strategies in South-Western Europe.
A perceptually motivated stationary wavelet packet filter-bank utilizing improved spectral over-subtraction algorithm for enhancing speech in non-stationary environments

This paper proposes a novel speech enhancement approach for a single-microphone system to meet the demand of quality noise reduction algorithms. The proposed system incorporates a perceptually motivated stationary wavelet packet filter-bank (PM-SWPFB) and improved spectral over-subtraction (I-SOS) algorithm together to enhance the speech degraded by non-stationary or colored noise environment. The PM-SWPFB is obtained by adjusting the uniformly spaced stationary wavelet packet tree in order to most closely mimic the critical-bands of the psycho-acoustic model. The PM-SWPFB is, firstly, used to decompose the input noisy speech signal into nonuniform sub-bands. Then, I-SOS algorithm is used to estimate of speech from each sub-band. The I-SOS algorithm uses a new noise estimation approach, to estimate noise power from each sub-band without the need of explicit speech silence detection. The sub-band noise estimate is updated by adaptively smoothing the noisy signal power. The smoothing parameter is controlled by a function of the estimated signal-to-noise ratio (SNR). The performance of the proposed speech enhancement system is evaluated objectively by SNR, Itakura-Saito distortion measure and subjectively by informal listening test. The results confirm that the proposed speech enhancement system is capable of reducing noise with little speech degradation remains acceptable in real-world environments, and the overall performance is superior to several competitive methods.
Ceftazidime-avibactam Versus Doripenem for the Treatment of Complicated Urinary Tract Infections, Including Acute Pyelonephritis: RECAPTURE, a Phase 3 Randomized Trial Program

There is an urgent need for new strategies to reduce carbapenem consumption. Ceftazidime-avibactam was highly effective for empiric treatment of complicated urinary tract infection, including in patients with ceftazidime-nonsusceptible pathogens, and may offer an alternative to carbapenems in this setting.
Analysis of multicell cooperation with random user locations via deterministic equivalents

We consider the uplink of a one-dimensional 2-cell network with fixed base stations (BSs) and randomly distributed user terminals (UTs). Assuming that the number of antennas per BS and the number of UTs grow infinitely large, we derive tight approximations of the ergodic sum rate with and without multicell processing for optimal and sub-optimal detectors. We use these results to find the optimal BS placement to maximize the system capacity. This work can be seen as a first attempt to apply large random matrix theory to the study of networks with random topologies. We demonstrate that such an approach is feasible and leads to analytically tractable expressions of the average system performance. Moreover, these results can be used to optimize certain system parameters for a given distribution of user terminals and to assess the gains of multicell cooperation.
Political Institutions and Growth Collapses

This paper tests whether Rodrik's (1999) results that institutions for conflict management are associated with the ability to react to economic shocks are robust to different ways of defining the quality of such institutions. We measure the quality of conflict management institutions with two different indices. The first is an index of political constraints on the ability of the executive to impose its will. These constraints limit the ability of the government to arbitrarily change the rules of the game and therefore may reduce redistributive struggles. The second index measures the degree of political particularism. We define political particularism as the policymakers' ability to further their career by catering to narrow interests rather than broader national platforms. The indices used in this paper solve the endogeneity and subjectivity biases that affect Rodrik's measure of institutional quality. We find strong support for the idea that high levels of political constraints and intermediate levels of political particularism are associated with a quick recovery from economic shocks.
Single-channel speech separation with memory-enhanced recurrent neural networks

In this paper we propose the use of Long Short-Term Memory recurrent neural networks for speech enhancement. Networks are trained to predict clean speech as well as noise features from noisy speech features, and a magnitude domain soft mask is constructed from these features. Extensive tests are run on 73 k noisy and reverberated utterances from the Audio-Visual Interest Corpus of spontaneous, emotionally colored speech, degraded by several hours of real noise recordings comprising stationary and non-stationary sources and convolutive noise from the Aachen Room Impulse Response database. In the result, the proposed method is shown to provide superior noise reduction at low signal-to-noise ratios while creating very little artifacts at higher signal-to-noise ratios, thereby outperforming unsupervised magnitude domain spectral subtraction by a large margin in terms of source-distortion ratio.
Robust speech/non-speech detection using LDA applied to MFCC for continuous speech recognition

Continuous speech recognition applications need precise detection because the number of words to recognize is unknown and vocabulary words can be short. The speech/non-speech detection must be robust to the boundary precision. In this work, a new approach to evaluate detection algorithm for continuous speech recognition is presented. The speech/non-speech detection using energy parameter combined with a Linear Discriminant Analysis (LDA) applied to Mel Frequency Cepstrum Coefficients (MFCC) is compared to the algorithm based on signal to noise ratio (SNR). The LDA applied to MFCC for speech/non-speech detection improves recognition performance in noisy environment and for continuous speech recognition applications.
Economics of religion on trial: how disestablishment did not lead to religious revival in the Swiss cantons of Geneva and Neuchâtel

Abstract According to ideas in contemporary economics of religion, religious disestablishment will lead to religious vitality: more strictness, more evangelising, and more growth. The present article puts this theory to the test by inspecting the historical record (1900 to the present) of the two Swiss cantons where disestablishment went farthest—Geneva and Neuchâtel—and by comparing them to other Swiss cantons where church and state remained closely linked. I find that the predictions of the economic model are not corroborated. Formerly established churches did not become stricter, did show increased, but relatively unsuccessful marketing efforts, did not grow, and became very poor financially. Non-established churches did not seem to benefit in any way from the disestablishment. The article makes four specific theoretical points that explain why this was the case.
Design and Development of Advanced Cavity-Based Dual-Mode Filters Using Low-Temperature Co-Fired Ceramic Technology for $V$-Band Gigabit Wireless Systems

In this paper, a novel concept of 3-D integrated -band dual-mode cavity filters, which permit the realization of a variety of quasi-elliptic responses by creating transmission zeros, has been demonstrated using multilayer low-temperature co-fired ceramic (LTCC) technology. A single-cavity resonator is designed to generate a degenerate resonance of two orthogonal modes ( and ), enabling dual-mode operation. The appearance and elimination of transmission zeros have been analyzed through the multipath coupling diagrams and lumped-element models. The quasi-elliptic dual-mode filters with the appropriate locations of the transmission zeros are then developed for receiver and transmitter channels of a -band transceiver module. Two pre-synthesized, dual-mode cavity filters are vertically stacked with two types of inter-coupling slots (1: rectangular, 2: cross) to realize the multipole filters for 60-GHz wireless local area network narrowband applications. These proposed filters are the first to be reported and have great potential to be integrated into miniaturized -band LTCC transceiver modules.
Constraints on the acquisition of variation

Individual languages exhibit variation in phonological structures both within and across words. This chapter examines the constraints placed on the acquisition of these stochastic phonological patterns. Theoretical perspectives on phonological acquisition are reviewed, revealing the importance of both formal and substantive constraints in a wide variety of learning theories. Empirical studies of the acquisition of variation are then reviewed. These results provide evidence that both formal and substantive constraints are active in the acquisition of variation. The integration of substantive constraints into theories of learning is then discussed, focusing on an extension of Warker and Dell’s (2006) connectionist proposal.
Effects of spam removal on search engine efficiency and effectiveness

Spam has long been identified as a problem that web search engines are required to deal with. Large collection sizes are also an increasing issue for institutions that do not have the necessary resources to process them in their entirety. In this paper we investigate the effect that withholding documents identified as spam has on the resources required to process large collections. We also investigate the resulting search effectiveness and efficiency when different amounts of spam are withheld. We find that by removing spam at indexing time we are able to decrease the index size without affecting the indexing throughput, and are able to improve search precision for some thresholds.
Admission Control for Aggregate Flow in Cloud Computing

With the development of cloud computing, the number and types of cloud services experience an explosive increase. Towards improving the Quality of Service provided in cloud computing, we model cloud computing’s admission control in this paper. Based on the observation that cloud service requests are typically concurrent, we propose admission control method for aggregate flow by computing the its effective bandwidth using network calculus. Acceptance decision is consequently made by computation with the effective bandwidth. Experiments are conducted to investigate properties of effective bandwidth, and to evaluate the performance of the admission control method under different settings.
The distinctive signatures of promoter regions and operon junctions across prokaryotes

Here we show that regions upstream of first transcribed genes have oligonucleotide signatures that distinguish them from regions upstream of genes in the middle of operons. Databases of experimentally confirmed transcription units do not exist for most genomes. Thus, to expand the analyses into genomes with no experimentally confirmed data, we used genes conserved adjacent in evolutionarily distant genomes as representatives of genes inside operons. Likewise, we used divergently transcribed genes as representative examples of first transcribed genes. In model organisms, the trinucleotide signatures of regions upstream of these representative genes allow for operon predictions with accuracies close to those obtained with known operon data (0.8). Signature-based operon predictions have more similar phylogenetic profiles and higher proportions of genes in the same pathways than predicted transcription unit boundaries (TUBs). These results confirm that we are separating genes with related functions, as expected for operons, from genes not necessarily related, as expected for genes in different transcription units. We also test the quality of the predictions using microarray data in six genomes and show that the signature-predicted operons tend to have high correlations of expression. Oligonucleotide signatures should expand the number of tools available to identify operons even in poorly characterized genomes.
Energy Efficient Multi-Layer Femtocell Networks

In this paper, we present an energy efficient routing algorithm for multi-layer femtocell networks. We consider a four-layered architecture that consists users, femtocells, relays, and macro base stations. The traffic to/from users passes through this architecture and is aggregated from/to the Internet through gateways in the relay layer. The traffic demand from users changes from time to time, so that some relays can be put into sleep mode in non-peak time to save energy. We propose a simple and effective routing algorithm to decide routes and active relays, to satisfy user traffic demand and save energy. Simulation results show that our proposed method outperforms benchmark schemes.