Miracle-dz/UniFAR-FTUs huggingface dataset:
More than just another crowd, we need a waiting line instead

The Shanghai World Expo attracted over 73 million visitors from May to October 2010 making it the most popular international exhibition in history. Aside from its many spectacular features, the Shanghai World Expo also became famous for its waiting lines, averaging over four hours for the most popular pavilions. This paper proposes an examination of those slow, too slow, human gatherings. From classical crowd psychology to the recent political theorizing of multitudes, the bulk of reflections carried forward on crowd phenomena have mainly paid attention to the (hyper)active, noisy, protesting crowds. In this article, I will use the example of these exceptional queues holding many thousands of longing visitors on the site of the 2010 World Expo in order to assert the need for an examination of the stagnant, inactive, and at times bored crowd. Another set of actors come into play: instead of riot control forces, Molotov cocktails, gas masks, barricades, and demonstrators, we have security guards, hats, umbrellas, water bottles, guardrails, watches, VIP passes, and customers.
MapReduce model for k-medoid clustering

Distributed and Parallel computing are best alternatives for scalable clustering of huge amount of data with moderate to high dimensions, together with improved speed up. In this paper we address the problem of k-medoid clustering using MapReduce framework for distributed computing on commodity machines to evaluate its efficacy. There are mainly two issues to be tackled. The first one is, how to distribute the data for efficient clustering and the second one is, how to minimize the I/O and network cost among the machines. So, the main contributions of this paper are : (a)A map reduce methodology for distributed k-medoid clustering; (b) Reduction in the overall execution time and the overhead of data movement from one site to another leading to sub linear scaleup and speedup. This approach proves to be efficient, as the local clustering can be carried out independently from each other. Experimental analysis on millions of data using just 10 cores in parallel shows the clustering of data of size 1M × 17 requires only 4 minutes. So, such low transmission cost and low bandwidth requirement leads to improved speedup and scaleup of the distributed data.
Prolonged post‐lumbar puncture cerebrospinal fluid leakage from lumbar subarachnoid space demonstrated by radioisotope myelography

SERIOUS COMPLICATIONS from lumbar puncture (LP) performed either as a diagnostic procedure or for anesthetic purposes are exceedingly rare. The most troublesome of complications, and by far the most common, is the postlumbar puncture headache. Kunkle et al.1 concluded that lumbar puncture headaches are the result of cerebrospinal fluid (CSF) leaking into the lumbar epidural space faster than it is being formed, producing an absolute reduction of the CSF volume. The decrease in CSF volume from a leakage below the cisterna magna results in a sagging of the brain. The downward movement of the brain when the patient is in an upright posture causes headache because the anchoring dura at the base of the brain is pain-sensitive on stretching. On the other hand, in the recumbent position, there is relief from the headache since the weight of the brain is shifted from the basal dura. The purpose of this communication is to report a case of severe post-LP headache due to an arachnodural rent demonstrated by radioisotope myelography.2
Discrete Wavelet Transform In Automatic ECG Signal Analysis

-The paper summarizes author's investigations in the field of ECG signal analysis, focused on QRS complex detection. Presented algorithm is based on the one described in [1]. Data containing electrocardiography signal (ECG) is processed by Discrete Wavelet Transform (DWT), computed at selected, characteristic scales, where QRS complex spectrum energy is the largest. For each transient present in the input signal coefficients of DWT produce localized extremes at several consecutive scales. This property is used in detection process. As characteristic scales are analyzed, the QRS waves can be found. Aligned positions of local extremes at characteristic scales determine the instant of QRS complex in the input signal. Only one QRS complex is detected per an iteration in the author's solution. This simplifies introducing: data blocks of variable length and threshold function of variable level. Each iteration besides QRS detection result ends with R-R interval instant and averaged value computation, R-R interval value dependent buffer length setup, threshold function update and data pointer update for the following iteration (which provide for necessary data overlapping). QRS detection fundamental parameters of the presented algorithm were calculated. These are: sensitivity: 99.86%; positive predictivity value: 99.91 % and additionally: error rate: 0.23 %; specificity: 99.91 % and reliability: 99.77%.
Representing Meaning with a Combination of Logical and Distributional Models

NLP tasks differ in the semantic information they require, and at this time no single semantic representation fulfills all requirements. Logic-based representations characterize sentence structure, but do not capture the graded aspect of meaning. Distributional models give graded similarity ratings for words and phrases, but do not capture sentence structure in the same detail as logic-based approaches. It has therefore been argued that the two are complementary.We adopt a hybrid approach that combines logical and distributional semantics using probabilistic logic, specifically Markov Logic Networks. In this article, we focus on the three components of a practical system:1 1) Logical representation focuses on representing the input problems in probabilistic logic; 2) knowledge base construction creates weighted inference rules by integrating distributional information with other sources; and 3) probabilistic inference involves solving the resulting MLN inference problems efficiently. To evaluate our approach, we use the task of textual entailment, which can utilize the strengths of both logic-based and distributional representations. In particular we focus on the SICK data set, where we achieve state-of-the-art results. We also release a lexical entailment data set of 10,213 rules extracted from the SICK data set, which is a valuable resource for evaluating lexical entailment systems.2
Nearly Optimal Competitive Online Replacement Policies

This paper studies the online replacement problem. In this problem an online player is engaged at each time in one activity. Associated with each activity are a changeover cost and flow rate. While involved in an activity the player's budget is depleted at the activity's flow rate. The player can switch to a new activity whenever it is offered but he pays a changeover cost. The player's goal is to decide when to switch activities so that his total cost is minimized. Typical applications are: equipment, jobs and supplier replacement, mortgage refinancing, etc. With respect to the competitive ratio performance measure, this paper seeks to determine the best possible competitive ratio achievable by an online replacement policy. Our results include the following: a general lower bound on the performance of any deterministic policy, a policy that is optimal in several special cases and a simple policy that is approximately optimal.
Wavelet-based speaker change detection in single channel speech data

Speaker segmentation is the task of ﬁnding speaker turns in an audio stream. We propose a metric-based algorithm based on Discrete Wavelet Transform (DWT) features. Principal component analysis (PCA) or linear discriminant analysis (LDA) [1] are further used to reduce the dimensionality of the feature space and remove redundant information. In the experiments our methods referred to as DWT-PCA and DWT-LDA are compared to the DISTBIC algorithm [2] using clean and noisy data of the TIMIT database. Especially, under conditions with strong noise, i.e. -10dB SNR, our DWT-PCA approach is very robust, the false alarm rate (FAR) increases by ∼ 2 % and the missed detection rate (MDR) stays about the same compared to clean speech, whereas the DISTBIC method fails – the FAR and MDR is almost ∼ 0 % and ∼ 100 % , respectively. For clean speech DWT-PCA shows an improvement of ∼ 30 % (relative) for both the FAR and MDR in comparison to the DISTBIC al-gorithm. DWT-LDA is performing slightly worse than DWT-PCA.
Cell Manipulation Attack Against Onion Services

In this study, we proposed OREA-OS, a cell manipulation attack devised to compromise Onion Services. Through the manipulation of cells, two collaborating nodes within a circuit exchange information to unveil the anonymity of the targeted Onion Service. We conducted an analysis of existing de-anonymization scenarios and effectively addressed the associated challenges, thereby achieving successful de-anonymization of Onion Services. To assess the efficacy of our attacks, we conducted experiments on both private and public Tor networks. The experimental results validate the effectiveness of our approach, as we accomplished 100% accurate identification of the relationship between domain names and Internet Protocol addresses, with no false positives. Within our simulated private network, the recall rate neared 100 %. On the public Tor network, the de-anonymization rate (98.6 %) exceeded the successful download rate (98.2 %). Furthermore, 99.2 % of success attacks took less than 10 seconds to confirm.
Misclassification, Correlation, and Cause of Death Studies

Relatives may tend to die of the same cause. A model is proposed specifying the degree of this association, simultaneously allowing for misclassification of cause of death. These mistakes usually degrade any existing correlation structure, the effects being marked when error rates reach between 20% to 30%. It is then that the search for associations becomes very difficult indeed, and results misleading. This is an example of a wider malaise that can afflict analysis of association, and the developments here apply to two-by-two contingency tables in general.
Clinically representative research in the psychological therapies: an emerging paradigm

This paper considers the tension between the ‘biology’ and the ‘therapeutic relationship’ camps within mental health nursing, which is focussed on differing conceptualisations of what it is that constitutes evidence and appropriate lines of inquiry. I argue that the struggle that mental health nurses have experienced in delivering evidence-based practice also resides in the thorny issue of methodological inquiry and how it is written into nursing practice. I would suggest that what is alienating to practitioners is the way in which evidence and evidence-based enquiry is generated. This paper offers a line of methodological inquiry that is based in clinical representativeness, a way of conducting and evaluating research to produce an evidence base that is informed from the ‘bottom up’ by ‘practice’. This paper not only contributes to the knowledge base of clinically representative research (CRR) but examines the ways in which this knowledge base has been produced and is currently perpetuated. The following themes are addressed: Processes and outcomes in CRR: I identify key treatment outcomes and processes operating in practice settings and consider with what confidence we can make conclusions on observed outcomes in these settings. I also examine key moderating and mediating processes influencing such outcomes. Practice of CRR: I reflect on the paradigm of CRR giving particular attention to how the paradigm has developed and is maintained. I look at how the relationship of CRR to effifficacy research has influenced paradigm development. Future directions of CRR: I summarise the conclusions of CRR to date and identify points of consensus, disagreement and clarity suggesting in what areas the field has moved forward and whether there are instances where points of conflict have contributed to growth.
I2R: Three Systems for Word Sense Discrimination, Chinese Word Sense Disambiguation, and English Word Sense Disambiguation

This paper describes the implementation of our three systems at SemEval-2007, for task 2 (word sense discrimination), task 5 (Chinese word sense disambiguation), and the first subtask in task 17 (English word sense disambiguation). For task 2, we applied a cluster validation method to estimate the number of senses of a target word in untagged data, and then grouped the instances of this target word into the estimated number of clusters. For both task 5 and task 17, We used the label propagation algorithm as the classifier for sense disambiguation. Our system at task 2 achieved 63.9% F-score under unsupervised evaluation, and 71.9% supervised recall with supervised evaluation. For task 5, our system obtained 71.2% micro-average precision and 74.7% macro-average precision. For the lexical sample subtask for task 17, our system achieved 86.4% coarse-grained precision and recall.
Giant Mitochondria in Pancreatic Acinar Cells of Alloxan-Induced Diabetic Rats

This was a study of the microscopic, ultrastructural, immunohistochemical, and enzyme cytochemical features of giant eosinophilic granules encountered in pancreatic acinar cells of alloxan-induced diabetic rats. Seven male F344 rats with diabetes induced by a single i.v. dose of alloxan were sacrificed after twenty-five weeks of treatment. Histologically, the pancreatic acini were diffusely atrophied, and the islets showed marked atrophy or had disappeared, and giant eosinophilic granules and small vacuoles were observed in almost all acinar cells. The eosinophilic granules showed negative reactions for periodic acid-Schiff (PAS) and acid phosphatase, as well as fat stains such as Nile blue, Oil red O, and Sudan III. Ultrastructurally, the giant eosinophilic granules were huge structures surrounded by a double membrane containing many irregular cristae. A large amount of small lipid droplets was also apparent in the basal area of the acinar cells. Immunohistochemical analysis of prohibitin, a kind of protein located in the mitochondrial inner membrane, was partially positive in the marginal area of some giant eosinophilic granules, but negative for the central area. The enzyme activity for succinic dehydrogenase (SDH), one of the mitochondrial enzymes, showed a localizing pattern similar to that of prohibitin. These findings confirmed that the giant eosinophilic granules in the exocrine pancreas of alloxan-induced diabetic rats were giant mitochondria.
Rapid Development of an Afrikaans English Speech-to-Speech Translator

In this paper we investigate the rapid deployment of a twoway Afrikaans to English Speech-to-Speech Translation system. We discuss the approaches and amount of work involved to port a system to a new language pair, i.e. the steps required to rapidly adapt ASR, MT and TTS component to AFrikaans under limited time and data constraints. The resulting system represent the first fully functional prototype built for Afrikaans to English speech translation.
Culture, resistance and policies of exclusion at World Cup 2014: the case of the ‘Baianas do Acarajé’

During the preparations for the Confederations Cup 2013 in Brazil, the International Federation of Association Football (FIFA) announced that it would restrict the sale of an important culinary tradition of the country, known as acarajé, during the 2014 World Cup games. Acaraje, which is listed by the Brazilian Government's Institute of National Historical and Artistic Heritage as intangible heritage – an adored fritter of beans, sauces, and shrimp – has been sold by Afro-Brazilian women around the Fonte Nova stadium in Salvador de Bahia for 60 years, with roots that stretch back to slavery. Based on its ‘Word Cup Law’ that creates ‘zones of exclusivity’ around stadiums and prohibits the practice of street vending during matches, FIFA announced a ban on the sale of acarajé within a two-kilometer radius of the stadium. This paper describes the campaign by a street vendor association against provisions in the FIFA World Cup Law, which exclude traditional sellers and allow only licensed products from tournament sponsors to be sold in proximity to World Cup stadiums, and discusses the impact of identity on this mobilization for social equality. Also highlighted is the role that social media played in the Baianas case, and the impact of these technologies on both protesters and media audiences.
Sociologie du contribuable et évitement de l'impôt

This article of fiscal sociology suggests an analytical review of the corpus of models and data relative to the avoidance (legal or not) of the tax so as to establish a cognitive theory of the rationality of the taxpayer. It aspires also to catch the attention of the sociologists for this promising field of research, though still neglected. On the basis of labelling theory of the deviance, of the tax revolt history and fiscal (social) psychology, the rational approach of the taxpayers insists on the importance of the concrete cognitive relation towards tax to explain the phenomena of tax avoidance (or not). It consists both in underlining the limits of the self-interest standard model and in emphasizing the political dimension of the taxation to give credence to the reality of a citizen's conception about the fair taxation (‘contribution-tax’) of the fiscal State in a given context. Cet article de sociologie fiscale propose un recensement analytique du corpus de modèles et de données relatifs à l'évitement (légal ou non) de l'impôt pour établir une théorie cognitive de la rationalité du contribuable. Il a aussi pour ambition de susciter l'attention des sociologues pour ce domaine de recherche prometteur, mais encore négligé. Partant de la théorie de l'étiquetage de la déviance, de l'histoire des révoltes fiscales et des résultats de la psychologic sociale de l'impôt, l'approche rationnelle du contribuable insiste sur l'importance de la relation cognitive concrète à l'impôt pour expliquer les phénomènes d'évitement fiscal (ou non). Il s'agit de marquer les limites du modèle utilitariste standard et de mettre en valeur la dimension politique de la fiscalité pour accréditer la réalité d'une conception citoyenne relative au juste prélèvement (“impôt-contribution”) de l'État fiscal dans un contexte donné. Dieser Aufsatz der Steuersoziologie präsentiert eine analytische Auswertung verschiedener Modelle und Daten bezüglich der ”Steuerverweigerung“ (legal oder illegal), um einekognitive Theorie der Rationalität des Steuerzahlers zu definieren. Der Auter will gleichzeitig die Aufmerksamkeit der Soziologen auf ein weitgehend vernachlässigstes Forschungsfeld lenken. Ausgehend von der Theorie der Verweigerungsformen, der Geschichte der Steuerrevolten und den Ergebnissen der (sozialen) Steuerpsychologie, zeigt die rationale Einstellung des Steuerzahlers die Bedeutung des konkreten kognitiven Verhältnisses zur Steuer und erklärt die Erscheinungsformen der Ver-weigerung in puncto Steuer oder nicht. Es ist hier entscheidend, die Grenzen des allgemeinen utilitaristischen Modells zu bestimmen und die politische Dimension der Steuerehebung eu betonen, um das Bestehen einer bürgerlichen Auffassung gerechter Abzüge (”Steuer-Beitrag“) durch den Fiskus in einem gegebenen Zusammenhang zu bestätigen.
The effects of peripheral exposure to information on brand preference

In this article, brand evaluations based on mere exposure to a brand name are compared to evaluations built on varying levels of cognitively processed brand information in a setting where all subjects have low involvement. Results indicate that a small but meaningfully sized group of subjects fully processed the information on brands they were exposed to, and rated those brands significantly higher than other brands where they had only seen the brand name alone. This finding was strongest for a fictional new brand, but also present for a well‐established brand. By contrast, the larger portion of low involvement subjects who did not fully process brand information, also did not rate brands significantly higher than their ratings for brands in which they saw no accompanying information. Implications for sponsors and advertisers are discussed.
Distributed Multirobot Exploration and Mapping

Efficient exploration of unknown environments is a fundamental problem in mobile robotics. We present an approach to distributed multirobot mapping and exploration. Our system enables teams of robots to efficiently explore environments from different, unknown locations. In order to ensure consistency when combining their data into shared maps, the robots actively seek to verify their relative locations. Using shared maps, they coordinate their exploration strategies to maximize the efficiency of exploration. This system was evaluated under extremely realistic real-world conditions. An outside evaluation team found the system to be highly efficient and robust. The maps generated by our approach are consistently more accurate than those generated by manually measuring the locations and extensions of rooms and objects
Anxiety, Methylphenidate Response, and Working Memory in Children With ADHD

Objective: To investigate the effects of methylphenidate (MPH) on components of working memory (WM) in children with ADHD and determine whether MPH produces differential effects on WM in children with comorbid anxiety (ANX). Method: Participants were a clinical sample of 130 children with ADHD, aged 6 to 12 years old (32% comorbid ANX). Each child participated in an acute randomized, double-blind, placebo-controlled, crossover trial with single challenges of three MPH doses. Four WM measures were used that varied in processing demands (storage versus manipulation of information) and modality (auditory—verbal; visual—spatial). Results: MPH improved auditory—verbal manipulation but only in the non-ANX children with ADHD. It had no effect on auditory—verbal storage of information. Also, MPH improved the ability to manipulate visual—spatial information in both ADHD groups, but beneficial effects on visual—spatial storage were evident only in children without comorbid ANX. Conclusions: Findings provide insight into potential mechanisms underlying individual differences in treatment response in ADHD, which may facilitate more targeted treatments. (J. of Att. Dis. 2008; 11(5) 546-557)
The One-Way Delay Measurement Algorithm on to Time Synchronization of NTP

In network measurement, one-way delay is an important network performance indicators, during the measurement, to synchronize the time of different nodes has a great influence on the results of measurement, especially in the large-scale network measurement. This paper propose a time synchronization stability comparison method based on NTP after research the time synchronization technology. In the one-way delay measurement, in order to eliminate measurement errors caused by the frequency difference between nodes, this paper propose a one-way delay corrective algorithm based on forward and reverse delay measurement after research existing time corrective algorithm. Finally, the measurement platform deployed in Planetlab and measure one-way delay. The measurement select more stable nodes based on NTP stability comparison algorithm, and correct one-way delay measurement results through clock corrective algorithm mentioned above. Experiments show that the results of corrective measurement algorithm are more accurate.
Feature selection in high dimensional regression problems for genomic

In the context of genomic selection in animal breeding, an important objective consists in looking for explicative markers for a phe- notype under study. In order to deal with a high number of markers, we propose to use combinatorial optimization to perform variable selection. Results show that our approach outperforms some classical and widely used methods on simulated and "closed to real" datasets.