Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Similarity from Collaborative Filters

Collaborative filtering methods (CF) exploit the wisdom of crowds to capture deeply structured similarities in musical objects, such as songs, artists or albums. When CF is available, it frequently outperforms content-based methods in recommendation tasks. However, songs in the so-called “long tail” cannot reap the benefits of collaborative filtering, and practitioners must rely on content-based methods. We propose a method for improving contentbased recommendation in the long tail by learning an optimized similarity function from a sample of collaborative filtering data. Our experimental results demonstrate substantial improvements in accuracy by learning optimal similarity functions.
Multidimensional signal space partitioning using a minimal set of hyperplanes for detecting ISI-corrupted symbols

A signal space partitioning technique is presented for detecting symbols transmitted through intersymbol interference channels. The decision boundary is piecewise linear and is made up of several hyperplanes. The goal here is to minimize the number of hyperplanes for a given performance measure, namely, the minimum distance between any signal and the decision boundary, Unlike in Voronoi partitioning, individual hyperplanes are chosen to separate signal clusters rather than signal pairs. The convex regions associated with individual signals, which together form the overall decision region, generally overlap or coincide among in-class signals. The technique leads to an asymptotically optimum detector when the target distance is set at half the minimum distance associated with the maximum-likelihood sequence detector. Complexity and performance can be easily traded as the target distance is a flexible design parameter.
From Armed Conflict to War: Ethnic Mobilization and Conflict Intensification*

This article presents a new line of inquiry into ethnicity and armed conflict, asking the question: are conflicts in which rebels mobilize along ethnic lines more likely to see intensified violence than nonethnically mobilized conflicts? The article argues that the ascriptive nature of ethnicity eases the identification of potential rebels and facilitates a rebel group’s growth, leading to an increased risk for war. This proposition is empirically tested using a Cox model on all intrastate armed conflicts 1946–2004; the results show that ethnically mobilized armed conflicts have a 92 percent higher risk for intensification to war. In extending the analysis, the study finds that the vast majority of conflicts intensified in the first year, but for every year a low-scale conflict remained active thereafter, the risk of intensification increased, peaking around year 12.
Do people become more apathetic as they grow older? A longitudinal study in healthy individuals

ABSTRACT Background: The aim of this study was to determine levels, rates and progression of apathy in healthy older persons and to investigate factors associated with its progression. Methods: Seventy-six healthy elderly subjects, aged 58–85 years (mean 69.9), who were recruited by general advertisement and through local community groups, participated as a control group for a longitudinal study of stroke patients. Data were collected on demographic, psychological, neuropsychological and neuroimaging (MRI) variables and apathy was rated by informants on the Apathy Evaluation Scale (AES). Results: Apathy scores and rates increased over 5 years, especially in men. Change of apathy was associated with informant ratings of cognitive decline in the years prior to baseline assessment but not to subsequent neuropsychological, neuroimaging or functional changes. Conclusions: Apathy increases with age in otherwise healthy community-dwelling individuals, particularly in men.
CSI: Compressed sensing-based clone identification in sensor networks

The clone detection, aiming to detect the illegal copies with all of the credentials of legitimate sensor nodes, is of great importance for sensor networks because of the substantial impact of clones on network operations like routing, data collection, and key distribution, etc. Based on a state-of-the-art signal processing technique, compressed sensing, we propose a novel clone detection method, called CSI. Not only is the design philosophy fundamentally different from the existing methods, but also it has the lowest communication cost among all detection methods. The performance and security of CSI will be demonstrated by numerical simulations and analyses.
Impact of litigation on senior clinicians: implications for risk management.

OBJECTIVES: To investigate the impact of litigation on consultants and senior registrars and to establish their views on methods of reducing adverse events and litigation. DESIGN: Postal survey. SETTING: Acute hospitals in the North Thames (West) Regional Health Authority. SUBJECTS: 1011 consultants and senior registrars in acute hospitals. MAIN MEASURES: Perceived causes and effects of adverse events; views on methods of reducing litigation and adverse events. RESULTS: 769 (76%) doctors responded. 288 (37%) had been involved in litigation at some point during their career; 213 surgeons (49%) and 75 (23%) doctors in the medical specialties. Anger, distress, and feeling personally attacked were common responses to litigation. Clinicians' views on reducing litigation emphasised the need for change at the clinical level. Supervision of junior staff, workload, and training in communication skills were to the fore. CONCLUSIONS: The high frequency of doctors who have experienced litigation and the emotional responses described indicate that clinicians require support at several levels. At a personal level, support can be offered to clinicians going through the litigation process or after an adverse event. Also, managerial support is needed by offering financial and practical help in correcting the factors that have been consistently identified as producing high risk situations to minimise the possibility of a reoccurrence. Accidents in medicine are, by their very nature, costly in human and financial terms and the root causes must be tackled. Recommendations are made for clinicians and risk management teams.
Trust, Staking, and Expectations

Trust is a kind of risky reliance on another person. Social scientists have offered two basic accounts of trust: predictive expectation accounts and staking (betting) accounts. Predictive expectation accounts identify trust with a judgment that performance is likely. Staking accounts identify trust with a judgment that reliance on the person's performance is worthwhile. I argue (1) that these two views of trust are different, (2) that the staking account is preferable to the predictive expectation account on grounds of intuitive adequacy and coherence with plausible explanations of action; and (3) that there are counterexamples to both accounts. I then set forward an additional necessary condition on trust (added to the staking view), according to which trust implies a moral expectation. When A trusts B to do x, A ascribes to B an obligation to do x, and holds B to this obligation. This Moral Expectation view throws new light on some of the consequences of misplaced trust. I use the example of physicians' defensive behavior/defensive medicine to illustrate this final point.
Program termination analysis in polynomial time

A size-change termination algorithm takes as input abstract information about a program in the form of size-change graphs and uses it to determine whether any infinite computation would imply that some data decrease in size infinitely. Since such an infinite descent is presumed impossible, this proves program termination. The property of the graphs that implies program termination is called SCT. There are many examples of practical programs whose termination can be verified by creating size-change graphs and testing them for SCT.The size-change graph abstraction is useful because the graphs often carry sufficient information to deduce termination, and at the same time are simple enough to be analyzed automatically. However, there is a tradeoff between the completeness and efficiency of this analysis, and complete algorithms in the literature can easily be pushed to an exponential combinatorial search by certain patterns in the graph structures.We therefore propose a novel algorithm to detect common forms of parameter-descent behavior efficiently. Specifically, we target lexicographic descent, multiset descent, and min- and max-descent. Our algorithm makes it possible to verify practical instances of SCT while guarding against unwarranted combinatorial search. It has worst-case time complexity cubic in the input size, and its effectiveness is demonstrated empirically using a test suite of over 90 programs.
The Effect of Emotional Content on Brain Activation and the Late Positive Potential in a Word n-back Task

Introduction There is mounting evidence for the influence of emotional content on working memory performance. This is particularly important in light of the emotion processing that needs to take place when emotional content interferes with executive functions. In this study, we used emotional words of different valence but with similar arousal levels in an n-back task. Methods We examined the effects on activation in the prefrontal cortex by means of functional near-infrared spectroscopy (fNIRS) and on the late positive potential (LPP). FNIRS and LPP data were examined in 30 healthy subjects. Results Behavioral results show an influence of valence on the error rate depending on the difficulty of the task: more errors were made when the valence was negative and the task difficult. Brain activation was dependent both on the difficulty of the task and on the valence: negative valence of a word diminished the increase in activation, whereas positive valence did not influence the increase in activation, while difficulty levels increased. The LPP also differentiated between the different valences, and in addition was influenced by the task difficulty, the more difficult the task, the less differentiation could be observed. Conclusions Summarized, this study shows the influence of valence on a verbal working memory task. When a word contained a negative valence, the emotional content seemed to take precedence in contrast to words containing a positive valence. Working memory and emotion processing sites seemed to overlap and compete for resources even when words are carriers of the emotional content.
Market Liquidity and Funding Liquidity

We provide a model that links an asset's market liquidity - i.e., the ease with which it is traded - and traders' funding liquidity - i.e., the ease with which they can obtain funding. Traders provide market liquidity, and their ability to do so depends on their availability of funding. Conversely, traders' funding, i.e., their capital and the margins they are charged, depend on the assets' market liquidity. We show that, under certain conditions, margins are destabilizing and market liquidity and funding liquidity are mutually reinforcing, leading to liquidity spirals. The model explains the empirically documented features that market liquidity (i) can suddenly dry up, (ii) has commonality across securities, (iii) is related to volatility, (iv) is subject to 'flight to quality', and (v) comoves with the market, and it provides new testable predictions.
Thinking about feeling : the nature and significance of the hot/cold empathy gap

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Benchmarking Violent Scenes Detection in movies

This paper addresses the issue of detecting violent scenes in Hollywood movies. In this context, we describe the MediaEval 2013 Violent Scene Detection task which proposes a consistent evaluation framework to the research community. 9 participating teams proposed systems for evaluation in 2013, which denotes an increasing interest for the task. In this paper, the 2013 dataset, the annotations process and the task's rules are detailed. The submitted systems are thoroughfully analysed and compared through several metrics to draw conclusions on the most promising techniques among which multimodal systems and mid-level concept detection. Some further late fusions of the systems are investigated and show promising performances.
A Regional and Social Dialectology of the BATH Vowel in South African English

Abstract This paper provides the beginnings of a pan–South African English dialectology, characterizing five cities (Cape Town, Port Elizabeth, Kimberley, Johannesburg, and Durban) and four ethnicities (Black, Colored, Indian, and White), via a single vowel, BATH (or /ɑ:/). From interviews with 200 selected speakers, 5553 tokens were subjected to acoustic analysis via PRAAT (Boersma & Weenink, 2010), yielding bivariate data on vowel quality. Statistical analysis via analysis of variance focused on sets of five persons in each of 40 city-ethnicity-gender combinations. Overall, no city shows cohesion across all ethnic groups, though Kimberley, the smallest of the cities, and Johannesburg, the largest, come close. Conversely, no ethnicity shows cohesion across all cities, although Black speakers of traditional L2 English background come close. There is a robust regional difference for Colored speakers between Johannesburg and the other cities. Gender effects are notable: women's means are closer to the historically prestige [ɑ:] variant than the historically broader variant [ɔ:] in 6 of 20 possible groupings by city and ethnicity; in none of the cases is the opposite true.
Suppression of mRNAs Encoding Tegument Tetraspanins from Schistosoma mansoni Results in Impaired Tegument Turnover

Schistosomes express a family of integral membrane proteins, called tetraspanins (TSPs), in the outer surface membranes of the tegument. Two of these tetraspanins, Sm-TSP-1 and Sm-TSP-2, confer protection as vaccines in mice, and individuals who are naturally resistant to S. mansoni infection mount a strong IgG response to Sm-TSP-2. To determine their functions in the tegument of S. mansoni we used RNA interference to silence expression of Sm-tsp-1 and Sm-tsp-2 mRNAs. Soaking of parasites in Sm-tsp dsRNAs resulted in 61% (p = 0.009) and 74% (p = 0.009) reductions in Sm-tsp-1 and Sm-tsp-2 transcription levels, respectively, in adult worms, and 67%–75% (p = 0.011) and 69%–89% (p = 0.004) reductions in Sm-tsp-1 and Sm-tsp-2 transcription levels, respectively, in schistosomula compared to worms treated with irrelevant control (luciferase) dsRNA. Ultrastructural morphology of adult worms treated in vitro with Sm-tsp-2 dsRNA displayed a distinctly vacuolated and thinner tegument compared with controls. Schistosomula exposed in vitro to Sm-tsp-2 dsRNA had a significantly thinner and more vacuolated tegument, and morphology consistent with a failure of tegumentary invaginations to close. Injection of mice with schistosomula that had been electroporated with Sm-tsp-1 and Sm-tsp-2 dsRNAs resulted in 61% (p = 0.005) and 83% (p = 0.002) reductions in the numbers of parasites recovered from the mesenteries four weeks later when compared to dsRNA-treated controls. These results imply that tetraspanins play important structural roles impacting tegument development, maturation or stability.
Solving the pre-image problem in kernel machines: A direct method

In this paper, we consider the pre-image problem in kernel machines, such as denoising with kernel-PCA. For a given reproducing kernel Hilbert space (RKHS), by solving the pre-image problem one seeks a pattern whose image in the RKHS is approximately a given feature. Traditional techniques include an iterative technique (Mika et al.) and a multidimensional scaling (MDS) approach (Kwok et al.). In this paper, we propose a new technique to learn the pre-image. In the RKHS, we construct a basis having an isometry with the input space, with respect to a training data. Then representing any feature in this basis gives us information regarding its pre-image in the input space. We show that doing a pre-image can be done directly using the kernel values, without having to compute distances in any of the spaces as with the MDS approach. Simulation results illustrates the relevance of the proposed method, as we compare it to these techniques.
Interface support for data archeology

I describe the IMA CS interface, which supports a type of interactive data exploration task called data archaeology. The interface facilitates users in performing this task using three key design principles: (1) combine power and ease of use, (2) provide direct support for integrated, itemtive data exploration, and (3) assist users in managing their work over time. I show how these principles are relevant in the data archaeology task, describe how knowledge representation technologyprovides a foundation for an adequate support system, and illustmte in detail how the interface offers powerful support for data archaeology.
Multidimensional Quantizers for Scalable Video Compression

Scalable video compression requires the creation of an encoded bit stream that may be decoded in part if channel bandwidth drops, decoder resources are limited, or a smaller image than the source is desired. A separable spatiotemporal subband decomposition is combined with vector and lattice quantizers modified so that the individual subbands may be decoded scalably. This results in finer bandwidth control and more flexibility than simply discarding entire subbands. >
Temporal preparation accelerates visual processing: Evidence from event-related brain potentials

Recent electrophysiological evidence shows that temporal preparation accelerates auditory perceptual processing, thus suggesting an attentional basis of temporal preparation. In the present study, we further investigated this possibility by measuring the effect of temporal preparation on visual perceptual processing. In an oddball paradigm, we presented frequent standards and infrequent deviants or targets, the latter one requiring a speeded response. Temporal preparation was manipulated via constant foreperiods. We observed that the latency of the N1 and the posterior N2 of the event-related potential, as indices of perceptual processing, were shortened by temporal preparation. This result shows that temporal preparation accelerates visual perceptual processing and strengthens the notion of an attentional mechanism underlying temporal preparation.
Resonant-tunneling diodes with emitter prewells

Resonant-tunneling diodes (RTDs) incorporating an emitter prewell structure are studied both theoretically and experimentally in order to investigate the utility of the emitter region as a device design parameter. The experiments show a tendency for peak bias, current, and the peak-to-valley ratio to increase for wider prewells, behavior likewise seen in both very simple and detailed calculations. Both the simple and more complete models point to interactions between states associated with the prewell and the main quantum well as the reasons for the increase in peak current. These results suggest design guidelines to affect peak bias, current, or the peak-to-valley ratio of RTDs.
A Real-Time Passenger Flow Estimation and Prediction Method for Urban Bus Transit Systems

Bus service is the most important function of public transportation. Besides the major goal of carrying passengers around, providing a comfortable travel experience for passengers is also a key business consideration. To provide a comfortable travel experience, effective bus scheduling is essential. Traditional approaches are based on fixed timetables. The wide adoptions of smart card fare collection systems and GPS tracing systems in public transportation provide new opportunities for using the data-driven approaches to fit the demand of passengers. In this paper, we associate these two independent data sets to derive the passengers’ origin and destination. As the data are real time, we build a system to forecast the passenger flow in real time. To the best of our knowledge, this is the first paper, which implements a system utilizing smart card data and GPS data to forecast the passenger flow in real time.
Bacterial Community Development in Experimental Gingivitis

Current knowledge of the microbial composition of dental plaque in early gingivitis is based largely on microscopy and cultural methods, which do not provide a comprehensive description of oral microbial communities. This study used 454-pyrosequencing of the V1–V3 region of 16S rRNA genes (approximately 500 bp), and bacterial culture, to characterize the composition of plaque during the transition from periodontal health to gingivitis. A total of 20 healthy volunteers abstained from oral hygiene for two weeks, allowing plaque to accumulate and gingivitis to develop. Plaque samples were analyzed at baseline, and after one and two weeks. In addition, plaque samples from 20 chronic periodontitis patients were analyzed for cross-sectional comparison to the experimental gingivitis cohort. All of the healthy volunteers developed gingivitis after two weeks. Pyrosequencing yielded a final total of 344 267 sequences after filtering, with a mean length of 354 bases, that were clustered into an average of 299 species-level Operational Taxonomic Units (OTUs) per sample. Principal coordinates analysis (PCoA) plots revealed significant shifts in the bacterial community structure of plaque as gingivitis was induced, and community diversity increased significantly after two weeks. Changes in the relative abundance of OTUs during the transition from health to gingivitis were correlated to bleeding on probing (BoP) scores and resulted in the identification of new health- and gingivitis-associated taxa. Comparison of the healthy volunteers to the periodontitis patients also confirmed the association of a number of putative periodontal pathogens with chronic periodontitis. Taxa associated with gingivitis included Fusobacterium nucleatum subsp. polymorphum, Lachnospiraceae [G-2] sp. HOT100, Lautropia sp. HOTA94, and Prevotella oulorum, whilst Rothia dentocariosa was associated with periodontal health. Further study of these taxa is warranted and may lead to new therapeutic approaches to prevent periodontal disease.
Outdoor-to-Indoor Propagation Characteristics of 850 MHz and 1900 MHz Bands in Macro-Cellular Environments

— Building penetration loss at 850 MHz and 1900 MHz bands in suburban environment is measured. The measurements are conducted in real GSM networks. Four buildings are studied aiming to provide first-order statistics of the signal coverage inside buildings. Results show that the mean building penetration loss for the ground floor is about 15 dB, with standard deviation of 3.5 dB. Additionally, the average rate of the change of penetration loss with height is 0.58 dB per meter. The results show also that building penetration loss may or may not depend on the operating frequency in different environments and propagation scenarios. 1900 MHz-band channels exhibit higher penetration loss values than 850 MHz-band ones by a mean of 2.8 dB.