Miracle-dz/UniFAR-FTUs huggingface dataset:
An algorithm for associating the features of two images

In this paper we describe an algorithm that operates on the distances between features in the two related images and delivers a set of correspondences between them. The algorithm maximizes the inner product of two matrices, one of which is the desired ‘pairing matrix ’ and the other a ‘proximity matrix ’ with elements exp (– r2ij/2σ2), where rij is the distance between two features, one in each image, and σ is an adjustable scale parameter. The output of the algorithm may be compared with the movements that people perceive when viewing two images in quick succession, and it is found that an increase in σ affects the computed correspondences in much the same way as an increase in interstimulus interval alters the perceived displacements. Provided that σ is not too small the algorithm will recover the feature mappings that result from image translation, expansion or shear deformation – transformations of common occurrence in image sequences – even when the displacements of individual features depart slightly from the general trend.
Modeling Self-Disclosure in Social Networking Sites

Social networking sites (SNSs) offer users a platform to build and maintain social connections. Understanding when people feel comfortable sharing information about themselves on SNSs is critical to a good user experience, because self-disclosure helps maintain friendships and increase relationship closeness. This observational research develops a machine learning model to measure self-disclosure in SNSs and uses it to understand the contexts where it is higher or lower. Features include emotional valence, social distance between the poster and people mentioned in the post, the language similarity between the post and the community and post topic. To validate the model and advance our understanding about online self-disclosure, we applied it to de-identified, aggregated status updates from Facebook users. Results show that women self-disclose more than men. People with a stronger desire to manage impressions self-disclose less. Network size is negatively associated with self-disclosure, while tie strength and network density are positively associated.
Cardiovascular effects of arginase inhibition in spontaneously hypertensive rats with fully developed hypertension.

AIMS Growing evidence suggests that arginase misregulation plays a key role in the pathophysiology of essential hypertension. In the present study, we investigated the potential cardiovascular therapeutic effects of a long-term treatment with an arginase inhibitor in adult spontaneously hypertensive rats (SHR) with fully developed hypertension. METHODS AND RESULTS Treatment of 25-week-old SHR with the arginase inhibitor N(omega)-hydroxy-nor-L-arginine (nor-NOHA, 40 mg/day for 10 weeks) sustainably reduced systolic blood pressure (-30 mmHg, P < 0.05). The antihypertensive effect of nor-NOHA was associated with changes on mesenteric artery reactivity including the restoration of angiotensin-II-induced contraction and acetylcholine-induced vasodilation to the values of normotensive Wistar Kyoto rats. Both nitric oxide synthase and cyclooxygenase-dependent mechanisms account for the improvement of endothelial function afforded by the arginase inhibitor, which in addition blunted hypertension-induced endothelial arginase I overexpression in mesenteric arteries. Nor-NOHA also prevented the remodelling of aorta as measured by collagen content and media/lumen ratio, and improved the compliance of carotid artery in SHR. Cardiac fibrosis assessed by collagen content of left heart ventricle was reduced by nor-NOHA, with no significant effect on cardiac hypertrophy. CONCLUSION Our results report that a long-term treatment with an arginase inhibitor reduced blood pressure, improved vascular function, and reduced cardiac fibrosis in SHR with fully developed hypertension. These data suggest that arginase represents a promising novel target for pharmacological intervention in essential hypertension.
An exploration of segmentation strategies in stream decoding

In this paper we explore segmentation strategies for the stream decoder - a method for decoding from a continuous stream of input tokens, rather than the traditional method of decoding from sentence segmented text. The behavior of the decoder is analyzed and modiﬁcations to the decoding algo-rithm are proposed to improve its performance. The experimental results show our proposed decoding strategies to be effective, and add support to the original ﬁndings that this approach is capable of approaching the performance of the underlying phrase-based machine translation decoder, at useful levels of latency. Our experiments evaluated the stream decoder on a broader set of language pairs than in previous work. We found most European language pairs were similar in character, and report results on English-Chinese and English-German pairs which are of interest due to the re-ordering required.
A Proposal for Improving Data Deduplication with Dual Side Fixed Size Chunking Algorithm

DeDuplication is the technique of data reduction by breaking streams of data down into very granular components, and storing only the first instance of data items on the destination media and all the other similar occurrences to an index. Hash values are computed to identify the similar data items. Fixed size chunking (FSC) is a DeDuplication algorithm which breaks the data into fixed size chunks or blocks from the beginning of the file. But the main disadvantage of this technique is that, if new chunks are added in front or in the middle of a file, remaining chunks will get shifted from its initial position. This will yields a new hash value to the resulting chunks and thereby less DeDuplication ratio. But we can overcome this drawback by calculating hash values of chunks from the beginning as well as from the end of file and storing both values to metadata table. A new algorithm 'Dual Side Fixed Size Chunking' is proposed to get the high DeDuplication ratio over existing FSC. Without using computationally expensive Variable size chunking or content defined chunking, this algorithm can be effectively used for video or audio files to achieve a better DeDuplication ratio. This data reduction will provide network bandwidth savings and the ability to store more data on a given amount of disk or cloud storage. Reduced storage requirements will result in lower storage management and energy costs.
Construction of a Japanese Relevance-tagged Corpus

This paper describes our corpus annotation project. The annotated corpus has relevance tags which consist of predicate-argument relations, relations between nouns, and coreferences. To construct this relevance-tagged corpus, we investigated a large corpus and established the specification of the annotation. This paper shows the specification and dicult tagging problems which have emerged through the annotation so far.
Influencing Factors Analysis and Spreading Suggestions of Online Bank in China

Although online bank is more and more important in the business, some customers still do not use it. Therefore, this paper analyzes some critical factors that may influence the use intention of online bank, including perceived usefulness, and perceived easy to use based on TAM model and perceived riskness and familiarity. Then this paper takes WELLS FARGO bank as an example which implements successfully in online bank field, and through analyzing its strengths to provide some suggestions to Chinese online banks.
Analyzing and Predicting Patterns of DAMSL Utterance Tags

We have been annotating TRAINS dialogs with dialog acts in order to produce training data for a dialog act predictor, and to study how language is used in these dialogs. We are using DAMSL dialog acts which consist of 15 independent attributes. For the purposes of this paper, infrequent attributes such as Unintelligible and Self-Talk were set aside to concentrate on the eight major DAMSL tag sets. For five of these eight tag sets, hand constructed decision trees (based solely on the previous utterance’s DAMSL tags) did better than always guessing the most frequent DAMSL tag values. This result suggests that it is possible to automatically build such decision trees especially if other sources of context are added. Our initial efforts to address our second goal (studying language use in the TRAINS dialogs) consist of measuring DAMSL tag cooccurrences and bigrams. Some interesting patterns have emerged from this simple analysis such as the fact that signaling non-understanding is often done through questions. These patterns suggest that we should also be considering an n-gram dialog act model for use in predicting DAMSL tags. Machine learning techniques have been successfully applied to speech recognition, part of speech tagging, word sense disambiguation, and parsing. One reason for this success is that researchers have been able to define "correct" answers even for word sense disambiguation (Miller et al. 1993) and parsing (Marcus, Santorini, & Marcinkiewicz 1992). DAMSL (Dialog Act Markup in Several Layers) is a system for labeling the "correct" dialog acts for an utterance. We are annotating dialogs with DAMSL tags in order to produce training data for a dialog act predictor, and to study how language is used in our dialog corpus. We start this paper with a brief description of DAMSL as well as a discussion of its suitability for encoding the "correct" dialog acts for an utterance. The second section of the paper discusses the motivation for using machine learning to automatically predict DAMSL tags, and the third section describes an initial attempt at constructing decision trees to predict DAMSL tags. The fourth section covers interesting tag co-occurrences and bigrams showing a few ways language is used in these dialogs and suggesting that a n-gram dialog act model may be the best approach for predicting DAMSL tags.
Prevention of antigenically drifted influenza by inactivated and live attenuated vaccines.

BACKGROUND The efficacy of influenza vaccines may decline during years when the circulating viruses have antigenically drifted from those included in the vaccine. METHODS We carried out a randomized, double-blind, placebo-controlled trial of inactivated and live attenuated influenza vaccines in healthy adults during the 2004-2005 influenza season and estimated both absolute and relative efficacies. RESULTS A total of 1247 persons were vaccinated between October and December 2004. Influenza activity in Michigan began in January 2005 with the circulation of an antigenically drifted type A (H3N2) virus, the A/California/07/2004-like strain, and of type B viruses from two lineages. The absolute efficacy of the inactivated vaccine against both types of virus was 77% (95% confidence interval [CI], 37 to 92) as measured by isolating the virus in cell culture, 75% (95% CI, 42 to 90) as measured by either isolating the virus in cell culture or identifying it through real-time polymerase chain reaction, and 67% (95% CI, 16 to 87) as measured by either isolating the virus or observing a rise in the serum antibody titer. The absolute efficacies of the live attenuated vaccine were 57% (95% CI, -3 to 82), 48% (95% CI, -7 to 74), and 30% (95% CI, -57 to 67), respectively. The difference in efficacy between the two vaccines appeared to be related mainly to reduced protection of the live attenuated vaccine against type B viruses. CONCLUSIONS In the 2004-2005 season, in which most circulating viruses were dissimilar to those included in the vaccine, the inactivated vaccine was efficacious in preventing laboratory-confirmed symptomatic illnesses from influenza in healthy adults. The live attenuated vaccine also prevented influenza illnesses but was less efficacious. (ClinicalTrials.gov number, NCT00133523.)
Reliably scalable name prefix lookup

Name prefix lookup is a core building block of information-centric networking (ICN). In ICN hierarchical naming schemes, each packet has a name that consists of multiple variable-length name components, and packets are forwarded based on longest name prefix matching (LNPM). LNPM is challenging because names are longer than IP addresses and the namespace is unbounded. Recently proposed solutions have shown encouraging performance, however, most are optimized for or evaluated with a limited number of URL datasets that may not fully characterize the forwarding information base (FIB). What's more, the worst-case scenarios of several schemes require O(k) string lookups, where k is the number of components in each prefix. Thus, the sustained performance of existing solutions is not guaranteed. In this paper, we present a LNPM design based on the binary search of hash tables, which was originally proposed for IP lookup. With this design, the worst-case number of string lookups is O(log(k)) for prefixes with up to k components, regardless of the characteristics of the FIB. We implemented the design in software and demonstrated 10 Gbps throughput with one billion synthetic longest name prefix matching rules, each containing up to seven components. We also propose level pulling to optimize the average LNPM performance based on the observation that some prefixes have large numbers of next-level suffixes in the available URL datasets.
ANALYSING A RIGHT-WING TEXT THROUGH HALLIDAY’S TRANSTIVITY SYSTEM AND CRITICAL DISCOURSE ANALYSIS

In this paper, I attempt to present an example of following Halliday’s grammatical system in analysing a text that can bear racial references. Doing so, the text analysis can be viewed from a critical discourse analysis perspective. The text chosen, titled “Europe Must Close Its Borders or be Swamped by Third World”, published in 2009, exhibits a typical example of the political rhetoric used by far-right political parties represented by one of its leaders in Britain, Nick Griffin. My assumption is that every word, every verb, and every phrase used is carefully chosen to convey the intended agendas of the party to its prospect voters in a clever way, which achieves its maximum effect with little or no apparent violation to the press guidelines. I also believe that such a stirring text, as far as the paper is concerned, would benefit from the use of various types of verbs and phrases that should suffice the requirement of the analysis. The paper may be of good use to students interested in studying this system of analysis as it deeply goes into the details of the used text.
Similarity between constituent words or phrases of metaphors

This study examined Ortony's (1979) model of asymmetric similarity between constituents of metaphors In Experiment I, 35 subjects rated the similarity of topic (subject) to vehicle (predcate) in 96 metaphorical and anomalous sentences (Noun-A is Noun-B). Another group of 32 subjects listed features (attribute-adjectives) of each topic or vehicle, and the salience of features was measured by their frequency of mention. Multiple regression analysis indicates that the saliences of common features and of distinctive features predict the rated similarity well. Multiple discriminant analysis indicates that metaphor, reversed metaphor and anomalous sentence are distinguished in the relative degrees of salience of common features, as predicted by Ortony's model. Experiment II manipulated the salience of common or distinctive features by applying nine types of adjective modification to topic or vehicle (e. g., Adjective Noun-A is Noun-B). Twenty-eight subjects ranked these metaphors according to the similarity of topic to vehicle, and another group of 28 subjects ranked the same set of metaphors according to the comprehensibility as well as the intensity of interest they felt in each metaphor. Results show that the adjectives which cue (make more salient) common features increase similarity and comprehensibility, while the adjectives which cue distinctive features decrease them, but increase metaphor interest. These results are consistent with Ortony's model.
Assessing the relationships among tag syntax, semantics, and perceived usefulness

With the recent interest in socially created metadata as a potentially complementary resource for image description in relation to established tools such as thesauri and other forms of controlled vocabulary, questions remain about the quality and reuse value of these metadata. This study describes and examines a set of tags using quantitative and qualitative methods and assesses relationships among categories of image tags, tag assignment order, and users' perceptions of usefulness of index terms and user‐contributed tags. The study found that tags provide much descriptive information about an image but that users also value and trust controlled vocabulary terms. The study found no correlation between tag length and assignment order, and tag length and its perceived usefulness. The findings of this study can contribute to the design of controlled vocabularies, indexing processes, and retrieval systems for images. In particular, the findings of the study can advance the understanding of image tagging practices, tag facet/category distributions, relative usefulness and importance of these categories to the user, and potential mechanisms for identifying useful terms.
Esophageal Acidification During Nocturnal Acid-breakthrough with Ilaprazole Versus Omeprazole in Gastroesophageal Reflux Disease

Background/Aims Though nocturnal acid-breakthrough (NAB) is common in gastroesophageal reflux disease (GERD) patients, its clinical importance results from esophageal acidification, which has been shown to be uncommon. Ilaprazole, a long-acting proton pump inhibitor, may cause NAB infrequently. Accordingly, we studied prospectively, (1) frequency and degree of esophageal acidification during NAB, and (2) frequency and severity of NAB while on ilaprazole versus omeprazole. Methods Fifty-eight consecutive patients with GERD on once daily ilaprazole, 10 mg (n = 28) or omeprazole, 20 mg (n = 30) for > one month underwent 24-hour impedance-pH monitoring prospectively. NAB was defined as intra-gastric pH < 4 for > one hour during night, and esophageal acidification as pH < 4 for any duration. Nocturnal symptoms (heartburn, regurgitation, and chest pain) were also recorded. Results Of the 58 patients (age 35.5 [inter-quartile range 26.5–46.0] years, 38 [65.5%], 42 (72.4%) had NAB. Though patients with NAB had lower nocturnal intra-gastric pH than without (2.8 [1.9–4.1] vs 5.7 [4.6–6.8], P < 0.001), frequency and duration of nocturnal esophageal acidification (17/42 vs 4/16, P = 0.360 and 0.0 [0.0–1.0] vs 0.0 [0.0–0.3] minutes, P = 0.260, respectively) and symptoms were comparable (13/42 vs 6/16, P = 0.750). Though ilaprazole was associated with less NABs (1 [range 1–2, n = 19] vs 1 [range 1–3, n = 23], P = 0.010) than omeprazole, the frequency, duration, and mean intra-gastric pH during NAB were comparable (19/28 vs 23/30, P = 0.560; 117 [0–315] vs 159 [69–287] minutes, P = 0.500; 1.02 [0.7–1.4] vs 1.04 [0.44–1.3], P = 0.620, respectively). Conclusions Though NAB was common while patients were on a proton pump inhibitor, esophageal acidification was uncommon. Frequency and severity of NAB were comparable among patients on ilaprazole and omeprazole, except for the lesser number of NABs with ilaprazole.
The nonlinear relationship of individual commitment to organizational change and behavioral support

This study examined the relationships between affective commitment to change (desire), normative commitment to change (obligation), and continuance commitment to change (cost), as predictors of behavioral support for change. Affective commitment to change and normative commitment to change both demonstrated curvilinear relationships with behavioral support. Continuance commitment to change did not. This study also used residualized relative importance analyses, techniques for a full decomposition of the variance in nonlinear regression models. The nonlinear models accounted for more of a change in variance than did the linear regression models. The discussion section includes a scatterplot diagram intended to bridge the gap between scholars and practitioners in that the figure illustrates a range of resistant to commitment behaviors that cause organizational change initiatives to fail. The conclusion provides recommendations for researchers regarding the inclusion of a nonlinear frame when designing organizational change studies, and recommendations for practitioners regarding the damage that compliance is responsible for in organizational change initiatives.
Design of Robust Superdirective Arrays With a Tunable Tradeoff Between Directivity and Frequency-Invariance

Frequency-invariant beam patterns are often required by systems using an array of sensors to process broadband signals. If the spatial aperture is shorter than the involved wavelengths, using a superdirective beamforming is essential to get an efficient system. In this context, robustness of array imperfections is a crucial feature. In the literature, only a few approaches have been proposed to design a robust, superdirective, frequency-invariant beamformer based on filter-and-sum architecture; all of them achieve frequency-invariance by imposing a desired beam pattern. However, the choice of a suitable desired beam pattern is critical; an improper choice results in unsatisfactory performance. This paper proposes a new method of array synthesis that allows the design of a robust broadband beamformer with tunable tradeoff between frequency-invariance and directivity, without the need for imposing a desired beam pattern. The latter is defined as a set of variables that do not depend on frequency and are included in the vector of variables to be optimized. To this end, a suitable cost function has been devised whose minimum can be found in closed form. Therefore, the method is analytical and computationally inexpensive. In addition, a technique that allows obtaining a beam pattern with a linear phase over frequency is described. The results show the effectiveness of the proposed method in designing robust superdirective beam patterns for linear arrays receiving far-field signals, with special attention to microphone arrays of limited aperture.
The Good Society Considered: The Economic Dimension

In our time we hear much of what is wrong with our economic world with the shortfalls in economic performance and general well-being. My purpose in this lecture is to ask what would be right: what is the nature, what are the requirements, of the good and achievable economy and polity. This is a time of intense and, indeed, dangerous disorder in the countries, notably those of the former Soviet Union, that are making their uncertain and difficult way to a different economic and political system. That is perhaps the greatest economic and political issue and challenge of our time, the one where failure will portend the greatest disaster. On this I will have a later word.