Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic Word Sense Disambiguation Algorithm

A novel unsupervised genetic word sense disambiguation (GWSD) algorithm is proposed in this paper. The algorithm first uses WordNet to determine all possible senses for a set of words, then a genetic algorithm is used to maximize the overall semantic similarity on this set of words. A novel conceptual similarity function combining domain information is also proposed to compute similarity between senses in WordNet. GWSD is tested on two sets of domain terms and obtains good results. A weighted genetic word sense disambiguation (WGWSD) algorithm is then proposed to disambiguate words in a general corpus. Experiments on SemCor are carried out to compare WGWSD with previous work.
The Federal GPRA Evaluation Mandate

Abstract The Government Performance and Results Act (GPRA) mandates inclusion of evaluation in federal agency strategic plans, impacting human service programs receiving federal support. Recommended evaluation methods include flexible ongoing and participatory approaches. Yet social work may not be prepared to appropriately respond to the government's demands for accountability. This paper reviews GPRA and its implications for social work practice, evaluation, and research, offering response strategies. The paper suggests that the creation of a National Center for Social Work Research (S. 70/H.R. 663) could help bridge evaluation gaps, offering a centralized mechanism for monitoring evaluation activities and maximizing federal research resources.
Signaling Quality: An Examination of the Effects of Marketing- and Nonmarketing-Controlled Signals on Perceptions of Automotive Brand Quality

When introducing new products to market, firms often leverage marketing signals in an effort to increase perceptions of product quality. While prior research mostly focuses on marketing-controlled signals that firms can directly influence to affect consumer perceptions of product quality, the proliferation of nonmarketing-controlled signals in the form of third-party product reviews introduces a new layer of complexity to a consumer's inference process. Given the fact that propagation of marketing signals and third-party reviews has made the marketplace more interactive, it is no longer diagnostic to analyze the impact of various quality signals on consumer perceptions, separately. The purpose of this study is twofold. There has been extant research on the individual effects of marketing-controlled signals on quality perception, but research providing a simultaneous examination of multiple signals is scarce. The first purpose is to examine interaction effects between various marketing signals on consumer perceptions of quality. Firms may be able to control the communication strategy of internal signals (e.g., price, advertising), but third-party signals are external to the firm, and hence are often perceived as being more credible and less biased than marketing signals. Despite the popularity of third-party product reviews, there is scarce empirical research about how they impact perceptions in the presence of marketing-controlled quality signals. Thus, the second purpose is to examine the interaction effects between marketing signals and independent third-party reviews on perceived product quality. This study advances existing models of market signaling to account for the potential interactions between various types of quality signals. Hypotheses are tested using a longitudinal data set comprising all car brands that have existed in the U.S. automotive industry between 1990 and 2007. The automotive industry provides an ideal context for the analyses as quality is an indispensable yet not easily discernible attribute of cars. Furthermore, consumer perceptions of the quality of new vehicle introductions can have a profound effect on product performance. Data are compiled from various secondary sources, including Harris Interactive's Equitrend, Consumer Reports, and TNS Media Intelligence, among others. Econometric techniques are used to estimate the empirical model. Findings show that effects of quality signals are codependent such that third-party quality ratings reduce the effectiveness of pricing and advertising, whereas they enhance the credibility of warranty signal. Furthermore, warranty positively interacts with price and advertising. It is also demonstrated that car sales in the previous period and the country of origin of the car brand significantly impact perceived quality. Overall, the research findings can help car manufacturers better understand how their initial product configurations and marketing strategies impact the perception of new vehicle introductions.
Krill Can Shrink as an Ecological Adaptation to Temporarily Unfavourable Environments

Because environments vary with both predictable patterns and with unpredictable but recurring events, ecologists have long been interested in the ecological adaptations that organisms use to survive periods in which the environment may be exceptionally harsh. In the northeast Pacific, one example of this is periodic warming episodes. Here, we demonstrate for the first time that krill (Euphausia pacifica Hansen), which is a centrally important species in coastal-upwelling systems, can survive periods of abnormally high temperatures by shrinkage between molts, even if food is plentiful. In addition, we demonstrate that there is a high amount of individual variation in growth rates of krill. Krill are centrally important within pelagic foodwebs both worldwide and within the northeast Pacific, thus we explore the potential ecological consequences of such shrinkage for both krill and their predators. Krill (euphausiids) form a key trophic link between primary producers and higher level consumers in oceanic food webs worldwide. Indeed, most marine species (including humans) are only one or two trophic levels away from krill. That is, they are either prey of krill, predators of krill or predators of krill predators. Euphausia pacifica Hansen is widely distributed throughout the northeast Pacific and is often the dominant (both in terms of numerical abundance and biomass) krill species within both oceanic and coastal-upwelling ecosystems (Brinton 1962). Along the west coast of North America it can be found from Alaska to as far south as 258N, where mean temperature in the top 250 m of the water column can be 158C and maximum surface temperatures can exceed 208C (Brinton 1976). Recruitment, growth and reproductive activity within populations of E. pacifica are known to correlate with seasonal patterns of primary productivity Because krill play a central role in pelagic food webs, their demography and life history can have important implications for community structure and function. Life history strategies are means that organisms use to achieve successful reproduction in uncertain environments. Consequently they must address components that may be relatively predictable on a variety of time scales as well as those that are recurring but relatively unpredictable. There is widespread consensus among ecologists that populations respond to climactic events that may alter northeast Pacific marine ecosystems on interannual (i.e. El NinÄ o) and interdecadal (i.e. Such events affect temperature, salinity, and patterns of nutrient input and can have profound and extended impacts throughout food webs Here we demonstrate that E. pacifica can …
Curry: A Truly Functional Logic Language

Functional and logic programming are the most important declarative programming paradigms, and interest in combining them has grown over the last decade. However, integrated functional logic languages are currently not widely used. This is due to the fact that the operational principles are not well understood and many diierent evaluation strategies have been proposed which resulted in many diierent functional logic languages. To overcome this situation, we propose the functional logic language Curry which can deal as a standard language in this area. It includes important ideas of existing functional logic languages and recent developments, and combines the most important features of functional and logic languages. Thus, Curry can be the basis to combine the currently separated research eeorts of the functional and logic programming communities and to boost declarative programming in general. Moreover, since functions provide for more eecient evaluation strategies and are a declarative replacement of some impure features of Prolog (in particular, pruning operators), Curry can be also used as a declarative successor of Prolog. 1 Motivation During the last decade, many proposals have been made to combine the most important declarative programming paradigms (see 13] for a survey). Functional logic languages ooer features from functional programming (reduction of nested expressions, higher-order functions) and logic programming (logical variables, partial data structures, search for solutions). Compared to pure functional languages, functional logic languages have more expressive power due to the use of logical variables and built-in search mechanisms. Compared to pure logic languages, functional logic languages have more eecient evaluation mechanisms due to the (deterministic! ) reduction of functional expressions. Thus, impure features of Prolog to restrict the search space, like the cut operator, can be avoided in functional logic languages. However, there is no obvious way to combine the search facilities of logic programming with eecient evaluation principles of functional programming. As a consequence, quite diierent methods to integrate functional and logic languages have been proposed in the past. The most promising operational principles are residuation and narrowing. Residuation is based on the idea to delay function calls until they are ready for deterministic evaluation. The residuation principle is used, for instance, in the languages Escher 19], Le Fun 2], Life 1], NUE-Prolog 27], and Oz 33]. Since the residuation principle evaluates function calls by deterministic reduction steps, nondeterministic search must be explicitly encoded by predicates
Fast structural matching for document image retrieval through spatial databases

The structure of document images plays a significant role in document analysis thus considerable efforts have been made towards extracting and understanding document structure, usually in the form of layout analysis approaches. In this paper, we first employ Distance Transform based MSER (DTMSER) to efficiently extract stable document structural elements in terms of a dendrogram of key-regions. Then a fast structural matching method is proposed to query the structure of document (dendrogram) based on a spatial database which facilitates the formulation of advanced spatial queries. The experiments demonstrate a significant improvement in a document retrieval scenario when compared to the use of typical Bag of Words (BoW) and pyramidal BoW descriptors.
Characterization of Geographic Distribution of Sensor Data by Opportunistic Network

In addition to blog and schedule sharing, sharing physical data, such as noise or temperature values, and event data, such as information recorded when purchasing at a shop, with other nodes located in a distributed manner enables new applications using geographic distribution. Geographic distribution of physical data of noise allows a user to see geographic trends, such as the location of quiet areas, and geographic distribution of event data of shop purchases allows a user to estimate the route for the shop. However, due to the immature ubiquity of dedicated sensor nodes used to detect physical and event data, it is not easy for a user to share physical and event data. In this paper, we propose a new characterization method to provide geographic distribution of physical and event data, by using a mobile phone as a sensor node, since mobile phones have gained wide acceptance. In this method, a mobile phone can share physical and event data with other mobile phones by using opportunistic networks, which may be composed of other mobile phones incidentally located within the transmission range of short distance wireless communication. Furthermore, we define new indicators to take the freshness of physical and event data into account, so that a user can grasp geographic trends in real time. We conducted a computer simulation to show how valuable geographic distribution can be characterized by the proposed method.
The Feldstein‐Horioka puzzle in an ARIMA framework

Purpose - To test the Feldstein-Horioka hypothesis that the investment-to-output ratio moves one-for-one with the saving-to-output ratio, suggesting international capital mobility. Design/methodology/approach - The paper uses the econometric framework developed by Fisher and Seater, interpreting the Feldstein-Horioka hypothesis as a long-run phenomenon, and paying particular attention to the integration properties of the data, since meaningful tests critically depend on these properties. The paper also investigates the power of the long-horizon regression tests, using the inverse power function of Andrews. Findings - The paper tests the Feldstein-Horioka hypothesis for 15 European countries, as well as for the USA and Japan, using annual data for the period from 1960 to 2002. Evidence is found against the Feldstein and Horioka hypothesis of low international capital mobility. Originality/value - Although the findings are in contrast to those of Feldstein and Horioka, they are consistent with neoclassical growth theory according to which there is no reason to expect a relation between saving and investment if there are no barriers to capital movements.
Characterization of 3,4-Methylenedioxymethamphetamine (MDMA) Enantiomers In Vitro and in the MPTP-Lesioned Primate: R-MDMA Reduces Severity of Dyskinesia, Whereas S-MDMA Extends Duration of ON-Time

l-3,4-Dihydroxyphenylalanine (l-DOPA) is the most effective treatment for Parkinson's disease, but long-term l-DOPA administration is marred by the emergence of motor complications, namely, dyskinesia and a shortening of antiparkinsonian benefit (wearing-OFF). 3,4-Methylenedioxymethamphetamine (MDMA) is unique in that it exerts antidyskinetic effects and may enhance antiparkinsonian actions of l-DOPA. MDMA is composed of two enantiomers with different pharmacological profiles; here, we describe a novel enantiospecific synthesis of the two enantiomers and expand on the previous characterization of their pharmacology. R-MDMA (rectus-MDMA) is relatively selective for 5-HT2A receptors, whereas S-MDMA (sinister-MDMA) inhibits both serotonin (SERT) and dopamine transporters (DAT; SERT/DAT ratio of 10 to 1). R- or S-MDMA (1, 3, and 10 mg/kg, s.c.) was administered in combination with l-DOPA (15 mg/kg, s.c.) to six female common marmosets (Callithrix jacchus) rendered parkinsonian by MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine) administration. Motor disability, including parkinsonism and dyskinesia, and duration of antiparkinsonian benefit (ON-time) were evaluated. After the administration of R-MDMA (3 and 10 mg/kg), the severity of peak-dose dyskinesia was decreased (by 33 and 46%, respectively; p < 0.05); although total ON-time was unchanged (∼220 min), the duration of ON-time with disabling dyskinesia was decreased by 90 min when compared to l-DOPA alone (69% reduction; p < 0.05). S-MDMA (1 mg/kg) increased the total ON-time by 88 min compared to l-DOPA alone (34% increase; p < 0.05), though dyskinesia were exacerbated. These data suggest that racemic MDMA exerts simultaneous effects, reducing dyskinesia and extending ON-time, by 5-HT2A antagonism and SERT-selective mixed monoamine uptake inhibition, which arise from its R and S enantiomers, respectively.
Characteristics of Body Fat, Body Fat Percentage and Other Body Composition for Koreans from KNHANES IV

Accurate measurement of fat mass has become increasingly important with the increasing incidence of obesity. We assessed fat and muscle mass of Koreans with the Korea National Health and Nutrition Examination Survey IV (KNHANES IV). We studied 10,456 subjects (aged 20 to 85 yr; 4,476 men, 5,980 women). Fat and muscle mass were measured by dual-energy x-ray absorptiometry. Reference values of body compositions were obtained using the LMS method. The fat mass index (FMI, body fat mass/height2; kg/m2) of Korean men did not correlate with age (P = 0.452), but those of Korean women (P < 0.001) did. The ratio of percentage of fat in the trunk and legs was positively related with age in both the genders. The appendicular lean mass/height2 (kg/m2) of Korean men was negatively related to age (P < 0.001). In women, this ratio increased with age (P < 0.001). When we defined obesity according to the FMI classification, the rates of obesity were 6.1% (FMI > 9 kg/m2) in men and 2.7% (FMI > 13 kg/m2) in women. It is concluded that the muscle mass decreases and obesity increases with aging in Korean men, whereas both fat mass and obesity increase with aging in Korean women.
Predicting smart home lighting behavior from sensors and user input using very fast decision tree with Kernel Density Estimation and improved Laplace correction

One way to predict the behavior of smart home lighting is by using machine learning. Currently many methods of supervised learning that used for this problem, one of them is decision tree method. Very Fast Decision Tree (VFDT) as one of the decision tree method that has advantages in online machine learning that may useful in smart home, but there are still some room of improvisation that can improve accuracy of VFDT. The experiment result is obtained that VFDT is better than Naïve Bayes (NB) and Artificial Neural Network (ANN) in offline and online experiment. In addition, Kernel Density Estimation (KDE) and improved Laplace correction that is used as improvisation of VFDT is able to increase the accuracy and Matthews Correlation Coefficient (MCC) of VFDT in predicting smart home lighting switch usage.
The efficacy of n-3 fatty acids DHA and EPA (fish oil) for perinatal depression

Depressive symptoms are common during pregnancy and the post-partum period. Although essential n-3 PUFA may have beneficial effects on depression, it remains unclear whether they are also effective for perinatal depression. The purpose of the present study was to assess the efficacy of n-3 supplementation for perinatal depression, by performing a meta-analysis on currently available data. After a thorough literature search, we included seven randomised controlled trials in the meta-analysis, all with EPA and/or DHA supplementation. Most studies were judged to be of low-to-moderate quality, mainly due to small sample sizes and failure to adhere to Consolidated Standards of Reporting Trials guidelines. Some studies were not primarily designed to address perinatal depression. A total of 309 women on n-3 fatty acid supplementation were compared with 303 women on placebo treatment. n-3 Supplementation was not found to be significantly more effective than placebo at post-treatment with a pooled effect size (Hedges's g) of − 0·03 (95 % CI − 0·18, 0·13; P = 0·76) using a fixed-effects model. Heterogeneity was low-to-moderate (I2 = 30 %). In a subgroup analysis of three small studies of pregnant women with major depression, there was some indication of effectiveness (effect size 0·17; 95 % CI − 0·21, 0·55). In conclusion, the question of whether EPA and DHA administration is effective in the prevention or treatment of perinatal depression cannot be answered yet. Future research should focus on women who are clinically depressed (or at risk). The quality of research in this area needs to improve.
Data rearrange based on mining block access sequence in Cloud Storage

In Cloud Storage system, storage systems have to service for large numbers of scattered data access nodes, and data I/O almost are in random access form, in addition, the distribution storage of data result in data transmission between the Cloud nodes increases greatly, then the performance of the cloud storage system was be restricted remarkably. In this paper, we put forward a system for improving access performance in Cloud Storage system. Through the access trace, the process which doing disk I/O should be detected. The processes that are executed contemporaneous should be regarded as a group. Then, the block access sequences belong to same process groups could be mined based on the Frequent Sequence Mining. And the block relation could be obtained. Ultimately, the related blocks could be rearranged to the near location. It could reduce the head moving of disk during access and realize the mapping from random access to sequence access partly. Furthermore, the data could be migrated between the storage nodes according to the block relation and reducing the data transfer through network between nodes. We have also evaluated the benefits of the system. Our result using real system workloads show that with the data rearrange and data transfer, about 10%–20% I/O response time could be reduced.
Inflation News and the Stock Market: Macroefficiency or Overreaction

Previous studies find only a weak relationship between inflation news and stock market returns. We show that significant daily market reactions to different types of inflation shocks occur in dynamic economic states. Also, although previous work has not examined longer-run market reactions, our results demonstrate large, significant, and slow market responses to both positive and negative inflation shocks in the post-event month. Stock return reversals are common in months subsequent to large market response to inflation shocks. In both daily and monthly analyses we find instances in which stock returns are not inversely related to inflation shocks. These and other findings lead us to conclude that inflation shocks are important news events that can produce a variety of stock market reactions depending on economic state and type of inflation shock. Our evidence also suggests that inflation shocks can generate stock market overreactions in some cases.
Web page repetitive structure and URL feature based Deep Web data extraction

Noise interference in web pages and the demand for multiple sample pages are the key issues of Deep Web data extraction. In this paper, we propose a novel web page repetitive structure and URL feature based approach for Deep Web data extraction. It employs continuous repetitive tag region and similar URL to partition the sample page into blocks, locate the data region and extract specific URL template, which is further exploited to quickly identify the data region and the boundary of data records in similar pages. Experimental results show that our approach is highly effective for Deep Web data extraction.
Dynamic analysis and control of a stewart platform manipulator

The Stewart platform is a six-axis parallel robot manipulator with a force-to-weight ratio and positioning accuracy far exceeding that of a conventional serial-link arm. Its stiffness and accuracy approach that of a machine tool yet its workspace dexterity approaches that of a conventional manipulator. In this article, we study the dynamic equations of the Stewart platform manipulator. Our derivation is closed to that of Nguyen and Pooran because the dynamics are not explicitly given but are in a step-bystep algorithm. However, we give some insight into the structure and properties of these equations: We obtain compact expressions of some coefficients. These expressions should be interesting from a control point of view. A stiffness control scheme is designed for milling application. Some path-planning notions are discussed that take into account singularity positions and the required task. The objective is to make the milling station into a semiautonomous robotic tool needing some operator interaction but having some intelligence of its own. It should interface naturally with part delivery and other higher-level tasks. 0 1993 John Wiley & Sons, Inc.