Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting the Compositionality of Nominal Compounds: Giving Word Embeddings a Hard Time

Distributional semantic models (DSMs) are often evaluated on artificial similarity datasets containing single words or fully compositional phrases. We present a large-scale multilingual evaluation of DSMs for predicting the degree of semantic compositionality of nominal compounds on 4 datasets for English and French. We build a total of 816 DSMs and perform 2,856 evaluations using word2vec, GloVe, and PPMI-based models. In addition to the DSMs, we compare the impact of different parameters, such as level of corpus preprocessing, context window size and number of dimensions. The results obtained have a high correlation with human judgments, being comparable to or outperforming the state of the art for some datasets (Spearman's ρ=.82 for the Reddy dataset).
No better ways to generate hard NP instances than picking uniformly at random

Distributed NP (DNP) problems are ones supplied with probability distributions of instances. It is shown that every DNP problem complete for P-time computable distributions is also complete for all distributions that can be sampled. This result makes the concept of average-case NP completeness robust and the question of the average-case complexity of complete DNP problems a natural alternative to P=? NP. Similar techniques yield a connection between cryptography and learning theory.
The teachable language comprehender: a simulation program and theory of language

The Teachable Language Comprehender (TLC) is a program designed to be capable of being taught to “comprehend” English text. When text which the program has not seen before is input to it, it comprehends that text by correctly relating each (explicit or implicit) assertion of the new text to a large memory. This memory is a “semantic network” representing factual assertions about the world. The program also creates copies of the parts of its memory which have been found to relate to the new text, adapting and combining these copies to represent the meaning of the new text. By this means, the meaning of all text the program successfully comprehends is encoded into the same format as that of the memory. In this form it can be added into the memory. Both factual assertions for the memory and the capabilities for correctly relating text to the memory's prior content are to be taught to the program as they are needed. TLC presently contains a relatively small number of examples of such assertions and capabilities, but within the system, notations for expressing either of these are provided. Thus the program now corresponds to a general process for comprehending language, and it provides a methodology for adding the additional information this process requires to actually comprehend text of any particular kind. The memory structure and comprehension process of TLC allow new factual assertions and capabilities for relating text to such stored assertions to generalize automatically. That is, once such an assertion or capability is put into the system, it becomes available to help comprehend a great many other sentences in the future. Thus the addition of a single factual assertion or linguistic capability will often provide a large increment in TLC's effective knowledge of the world and in its overall ability to comprehend text. The program's strategy is presented as a general theory of
Publisher click fraud in the pay-per-click advertising market: Incentives and consequences

Pay-per-click (PPC) advertising is being seriously threatened by the click fraud (CF). In this paper, we report a game-theoretic analysis of the incentives and consequences of CF involving Web content publishers. We find that the publisher competition induces CF, harming the efficiency especially the publisher payoff allocation in the market.
The Effects of modal-based endogenous attention on sound-induced flash illusion

affected by attention ( p s > 0.05). In addition, we also pooled the response counts across all of the participants and for both fission and fusion stimuli. The results showed that the odds ratio for fission was greater than that for fusion, and there was a difference among the three experiments for fission (17.5 vs. 9 vs. 21.95), and no effect for fusion (4.95 vs. 3.15 vs. 4.13). The results indicated that modal-based endogenous attention can affect the occurrence of fission illusions but does not affect the occurrence of fusion illusions. The present study provides insight into the top-down factors that can modulate sound-induced flash illusions.
Robust controller design for time-varying uncertainties using DK-iteration

In teleoperation systems for robot-assisted surgery there is typically interaction with time-varying uncertain environment and human-operator dynamics. By modeling these dynamics with an uncertain plant model, DK-iteration can be applied to synthesize controllers that are robust against these uncertain dynamics. The DK-iteration algorithm is readily available within MATLAB. However, the current implementation of the DK-iteration algorithm is based on the generalized Nyquist stability criterion which is only applicable to time-invariant dynamics. In this work, an analysis is made to identify the limitations of the DK-iteration with respect to time-varying uncertainties. An alternative approach, based on linear matrix inequalities, is proposed to make the DK-algorithm applicable to time-varying systems. An implementation in MATLAB is made and compared with the original algorithm.
A Simulation-Based Study on Performance Profit of Concurrent Multi-Path Transmission Schemes

The authors investigate the performance profit of concurrent multi-path transmission (CMT) schemes of Stream Control Transmission Protocol (SCTP) over various network environments. The results of simulation show that the performance profit of CMT-SCTP schemes strongly depends on network conditions (e.g., bandwidth). This implies that there are still a lot of studies to be needed on how to effectively use CMT-SCTP schemes over wireless networks.
Bayesian Exploration for Intelligent Identification of Textures

In order to endow robots with human-like abilities to characterize and identify objects, they must be provided with tactile sensors and intelligent algorithms to select, control, and interpret data from useful exploratory movements. Humans make informed decisions on the sequence of exploratory movements that would yield the most information for the task, depending on what the object may be and prior knowledge of what to expect from possible exploratory movements. This study is focused on texture discrimination, a subset of a much larger group of exploratory movements and percepts that humans use to discriminate, characterize, and identify objects. Using a testbed equipped with a biologically inspired tactile sensor (the BioTac), we produced sliding movements similar to those that humans make when exploring textures. Measurement of tactile vibrations and reaction forces when exploring textures were used to extract measures of textural properties inspired from psychophysical literature (traction, roughness, and fineness). Different combinations of normal force and velocity were identified to be useful for each of these three properties. A total of 117 textures were explored with these three movements to create a database of prior experience to use for identifying these same textures in future encounters. When exploring a texture, the discrimination algorithm adaptively selects the optimal movement to make and property to measure based on previous experience to differentiate the texture from a set of plausible candidates, a process we call Bayesian exploration. Performance of 99.6% in correctly discriminating pairs of similar textures was found to exceed human capabilities. Absolute classification from the entire set of 117 textures generally required a small number of well-chosen exploratory movements (median = 5) and yielded a 95.4% success rate. The method of Bayesian exploration developed and tested in this paper may generalize well to other cognitive problems.
Analysis of two-point statistics of cosmic shear. II. Optimizing the survey geometry

We present simulations of a cosmic shear survey and show how the survey geometry influences the accuracy of determination of cosmological parameters. We numerically calculate the full covariance matrices $\mbox{Cov}$ of two-point statistics of cosmic shear, based on the expressions derived in the first paper of this series. The individual terms are compared for two survey geometries with large and small cosmic variance. We use analyses based on maximum likelihood of $\mbox{Cov}$ and the Fisher information matrix in order to derive expected constraints on cosmological parameters. As an illustrative example, we simulate various survey geometries consisting of 300 individual fields of $13^\prime \times 13^\prime$ size, placed (semi-)randomly into patches which are assumed to be widely separated on the sky and therefore uncorrelated. Using the aperture mass statistics $\left\langle M_{\rm ap}^2 \right\rangle$, the optimum survey consists of 10 patches with 30 images in each patch. If $\Omega_{\rm m}, \sigma_8$ and Γ are supposed to be extracted from the data, the minimum variance bounds on these three parameters are 0.17, 0.25 and 0.04 respectively. These variances increase slightly when the initial power spectrum index n s is also to be determined from the data. The cosmological constant is only poorly constrained.
Convergence of weighted polynomial multiple ergodic averages

We study here weighted polynomial multiple ergodic averages. A sequence of weights is called universally good if any polynomial multiple ergodic average with this sequence of weights converges in $L^{2}$. We find a necessary condition and show that for any bounded measurable function $\phi$ on an ergodic system, the sequence $\phi(T^{n}x)$ is universally good for almost every $x$. The linear case was understood by Host and Kra.
Tensions in antibiotic prescribing

AbstractBACKGROUND: To reduce the prevalence of antibioticresistant bacteria in the community, physicians must optimize their use of antibiotics. However, optimal use from the perspective of the community (reserving newer agents for future use) is not always consistent with optimal use from the perspective of the individual patient (prescribing newer, broader agents). OBJECTIVES: To identify preferred patterns of antibiotic prescribing for patients with community-acquired pneumonia (CAP), measure explicit attitudes toward antibiotics and antibiotic resistance, and determine the relationship between these prescribing patterns and attitudes. DESIGN: Cross-sectional anonymous mail survey. PARTICIPANTS: National random sample of 400 generalist physicians (general internal medicine and family practice) and 429 infectious diseases specialists. MEASUREMENTS: Rank ordering of antibiotic preferences for a hypothetical outpatient with CAP and reasons for antibiotic selection. Endorsement of attitudes regarding antibiotic prescribing decisions and resistance. RESULTS: Both generalists and infectious diseases specialists were more likely to prefer newer, broader drugs for the treatment of CAP compared to older agents still recommended by national guidelines. Physicians rated the issue of contributing to antibiotic resistance lowest among 7 determinants of their choices. CONCLUSIONS: Despite national guidelines and increasing public awareness, the public health concern of contributing to the problem of antibiotic resistance does not exert a strong impact on physician prescribing decisions for CAP. Future efforts to optimize antibiotic prescribing decisions will need to consider options for increasing the impact of public health issues on the patient-oriented decisions of individual physicians.
SCAS-IS: Knowledge Extraction and Reuse in Multiprocessor Task Scheduling Based on Cellular Automata

Static Task Scheduling Problem (STSP) in multiprocessors is a NP-Complete problem. Cellular Automata (CA) have been recently proposed to solve STSP. The main feature of CA-based models to STSP is the extraction of knowledge while scheduling an application and its subsequent reuse in other instances. Previous works showed this approach is promising. However some desirable features have not been successfully exploited yet, such as: (i) the usage of an arbitrary number of processors, (ii) the massive parallelism inherent to CA and (iii) the reuse of evolved rules with competitive results. This paper presents a new model called SCAS-IS (Synchronous Cellular Automata Scheduler with Initialization Strategies). Its major innovation is the employment of fixed initialization strategies to start up CA dynamics. Parallel program graphs found in literature and others randomly generated were used to test the new model. Results show SCAS-IS overcame related models both in make span obtained as computational performance. It is also competitive with meta-heuristics.
Ubiquitin-dependent folding of the Wnt signaling coreceptor LRP6

Many membrane proteins fold inefficiently and require the help of enzymes and chaperones. Here we reveal a novel folding assistance system that operates on membrane proteins from the cytosolic side of the endoplasmic reticulum (ER). We show that folding of the Wnt signaling coreceptor LRP6 is promoted by ubiquitination of a specific lysine, retaining it in the ER while avoiding degradation. Subsequent ER exit requires removal of ubiquitin from this lysine by the deubiquitinating enzyme USP19. This ubiquitination-deubiquitination is conceptually reminiscent of the glucosylation-deglucosylation occurring in the ER lumen during the calnexin/calreticulin folding cycle. To avoid infinite futile cycles, folded LRP6 molecules undergo palmitoylation and ER export, while unsuccessfully folded proteins are, with time, polyubiquitinated on other lysines and targeted to degradation. This ubiquitin-dependent folding system also controls the proteostasis of other membrane proteins as CFTR and anthrax toxin receptor 2, two poor folders involved in severe human diseases. DOI: http://dx.doi. org/10.7554/eLife.19083. 001
Bounded creativity: understanding the restrictions on creative work in advertising agencies

The theme of creativity has gained prominence among practitioners and academics, and the emergence of creative industries, which combine creativity and commercial logic, has rendered the topic even more relevant. Creativity is frequently associated with the existence of flexible organizational structures and organizational cultures that favor autonomy and freedom of action. However, organizations commonly impose limits on the actions of creative professionals because of the timescales, budgets, and business and customer demands inherent to the organizational context. Knowledge of creativity in academia has advanced considerably in recent decades. However, empirical studies investigating the restrictions imposed on creative work in organizations are lacking. This study addresses this gap in the literature. Our objective was to investigate creativity within advertising agencies, a creative industry sector. The results reveal that creativity in such environments is marked by collective work, conditioned by time pressures for performing tasks, and influenced by the tension that originates from the interaction between two dimensions: the search for originality and the need for acceptance. On the basis of this research, we propose the concept of bounded creativity, which reflects the weakening of the creative experience in organizations.
Peculiar velocities of galaxies and clusters

We present a simple model for the shape of the distribution function of galaxy peculiar velocities. We show how both non-linear and linear theory terms combine to produce a distribution which has an approximately Gaussian core with exponential wings. The model is easily extended to study how the statistic depends on the type of particle used to trace the velocity field (dark matter particles, dark matter haloes, galaxies), and on the density of the environment in which the test particles are located. Comparisons with simulations suggest that our model is accurate. We also show that the evolution of the peculiar velocities depends on the local, rather than the global, density. Since clusters populate denser regions on average, using cluster velocities with the linear theory scaling may lead to an overestimate of the global value of Ω0. Conversely, using linear theory with the global value of Ω0 to scale cluster velocities from the initial to the present time results in an underestimate of their true velocities. In general, however, the directions of motions of haloes are rather well described by linear theory. Our results help to simplify models of redshift-space distortions considerably.
Cerebral blood flow SPECT imaging in right hemisphere-damaged patients with hemispatial neglect. A pilot study.

BACKGROUND Hemispatial neglect is characterised as a failure by a brain-damaged patient to attend to contralesional space. It is hypothesised to be a result of damage to a network involving the frontal, parietal and cingulated cortices, basal ganglia and thalamus. MATERIAL AND METHODS The aim of this preliminary study was to verify this model of neglect in 22 right hemisphere-damaged acute stroke patients, using single photon emission-computed tomography (SPECT). The presence of a single right-sided vascular brain lesion was confirmed on CT and/or MRI. Hemispatial neglect, assessed with a battery of drawings, line bisection and line and shape cancellation tests, was observed in 12 cases. RESULTS Patients with neglect (compared with those without neglect) had more extensive hypoperfusion in the frontal and parietal cortex, as well as striatum and thalamus. Left-sided hypoperfusion in the parietal cortex and the thalamus was also significantly associated with neglect on SPECT imaging. Performance in three out of five psychological tasks commonly used to detect the presence of hemispatial neglect, such as drawing tests and line bisection test, was exclusively linked with damage to the parietal cortex of the right hemisphere, while the line cancellation test might be attributable to the lesion of the right striatum. CONCLUSIONS These findings support the model attributing hemispatial neglect to a unilateral defect in a cortico-striatothalamo-cortical loop. CBF SPECT imaging may provide a reliable description of the brain pathology associated with hemispatial neglect.
Particle Swarms as Video Sequence Inhabitants For Object Tracking in Computer Vision

A solution based on a swarm intelligence metaphor with a prey-predator scheme is proposed for real time object tracking in video sequences, which is a basic process in multiple computer vision tasks. Swarm predator particles fly on a Boid-like fashion over image prey pixels, using combined image features to guide individual movement rules. Object tracking emerges from interaction between predator particles and their environment. The paper includes method's description and experimental evaluations on video streams that illustrate the efficiency of swarm based methods in different vision tasks
Intra line copy for HEVC screen content coding

This paper presents an intra line copy mode, which introduces a finer-granularity block partitioning structure for the intra copying technique, to further improve the coding efficiency for screen content. This mode first divides a prediction block horizontally or vertically into 1-pixel-wide lines and then operates intra copying line-by-line from the reconstructed pixels in the current frame. It shares some parallels with the notion of string matching widely used for lossless data compression. It, however, is more compliant to the current HEVC design and is parallel-friendly. This paper shall detail its various design issues, including the design of a fast algorithm based on hashing techniques and the impact of search window size on its performance and complexity trade-off. Experimental results show that the proposed mode can offer 2.7-12.9% of BD-rate reductions, with 26% increase of encoding runtime while keeping the decoding runtime unchanged, when integrated into the SCM-1.0 test model.
Nitrite Assessment of Processed Meat Products Commonly Consumed in Ghana

Sodium and potassium salts of nitrite are used in meat products as preservative, antioxidant and colour fixative. However, high levels of these chemicals pose risks such as toxicity due to the formation of nitroso compounds originated from nitrite sources. The present study was conducted to assess the nitrite residual levels and to evaluate the health risk of consumers from exposure of nitrite in commonly consumed processed meat products (sausage, corned beef and bacon) on the Ghanaian market. A total of 300 questionnaires were administered to various age groups in the study population in the Ayawaso West Sub Metro, Accra. Participants were made to fill out the 24 h food frequency questionnaire. Fifty (50) different types and brands of processed meat products were randomly selected and analyzed for nitrite residues by spectrophotometric method. The effect of boiling, frying and grilling as cooking methods commonly employed were investigated. The mean nitrite content in the samples was 139.85 mg/kg and the mean daily intake estimated at 114.89 mg/kg/day. Significantly, the nitrite levels found in this study was higher than the WHO/EU recommended levels of 125 mg/kg in processed meat. First order Monte Carlo simulation at 10,000 iterations estimated chronic daily intake of nitrite as 5.05 mg/kg/day. Subsequently, the average risk of consumption of processed meat within the limits of reference dose of nitrite (0.33 mg/Bw/day) for the studied population was estimated at 15.65 (>>1) indicating of adverse health effect to the consumers. Overall, boiling was safer cooking method for cured meat and sausages found on the Ghanaian market.
The value of provocation methods in patients suspected of having non-epileptic seizures

Non-epileptic seizures (NES) are reported in 18-23% of patients referred to comprehensive epilepsy centres. Non-epileptic seizures may also be present in 5-20% of the patients who are diagnosed as having refractory seizures. Because of their prevalence, financial and psychosocial outcomes cannot be ignored and accurate diagnosis is of the utmost importance. Various methods of seizure induction have been developed with the aim of differentiating epileptic from non-epileptic seizures. However, recording the attacks by video-EEG monitoring is the gold standard. In our outpatient EEG laboratory we try to induce seizures with verbal suggestion or IV saline infusion in patients who are referred by a clinician with the diagnosis of probable non-epileptic seizures. In this study we investigated the results of 72 patients who were referred between January 1992-June 1996. Non-epileptic seizures were observed in 52 (72.2%) patients. Thirteen of these patients still had risk factors for epilepsy. We could not decide whether all of their previous attacks were non-epileptic because 10-30% of the patients with NES also have epileptic seizures. For a more accurate diagnosis it was decided that these 13 patients, together with the 20 patients who did not have seizures with induction, needed video-EEG monitoring. Thirty-nine patients who had NES and no risk factors for epilepsy were thought to have pure non-epileptic seizures. We claim that not all patients suspected of having NES need long-term video-EEG monitoring and almost half (54.2%) of the cases can be eliminated by seizure induction with some provocative techniques.