Miracle-dz/UniFAR-FTUs huggingface dataset:
Toward Google borders

Query logs let by user on search-engines have helped create efficient tools for trend analysis, from commercial use to forecasting epidemics. In this paper, we propose a new method and system for cultural trends analysis based on Google auto-complete suggestions. We present Zeitgeist Borders, a toolkit enabling any user to collect and analyze associations between queries, suggestions and various regions of the world. We report unexpected observations about several behavioural and geographical trends along with promising uses.
In-Situ Data Quality Assurance for Environmental Applications of Wireless Sensor Networks

We present a local, distributed algorithm to detect measurement errors and infer missing readings in environmental applications of wireless sensor networks. To bypass issues of non-stationarity in environmental data streams, each sensor-processor node learns statistical distributions of differences between its readings and the readings of its neighbors, as well as differences between its current and previous readings. Scalar physical quantities such as air temperature, soil moisture, and light flux naturally display a great degree of spatiotemporal coherence, which in turn leads to a spectrum of fluctuations between adjacent or consecutive measurements characterized by small variances. This permits stable estimation over a small state space. The estimated distributions of differences are then used in statistical significance tests that exclude rare random errors in measurements at any single sensor, and to infer missing readings. Compared to an alternative method based on Bayesian classifiers, our algorithm is more storage-efficient, learns faster, and is more robust in the face of non-stationary phenomena. Field results from a wireless sensor network (Sensor Web) deployed at Sevilleta National Wildlife Refuge are presented.
Adaptive set intersections, unions, and differences

Motivated by boolean queries in text database systems, we consider the problems of finding the intersection, union, or difference of a collection of sorted sets. While the worst-case complexity of these problems is straightforward , we consider a notion of complexity that depends on the particular instance. We develop the idea of a proof that a given set is indeed the correct answer. Proofs, and in particular shortest proofs, are characterized. We present adaptive algorithms that make no a priori assumptions about the problem instance, and show that their running times are within a constant factor of optimal with respect to a natural measure of the difficulty of an instance. In the process, we develop a framework for designing and evaluating adaptive algorithms in the comparison model. 1 Introduction and Overview Our work can be seen in the general context of performing searches quickly in a database or data warehousing environment. The broad issue is that of characterizing what type of join operations can be performed without scanning the relations involved or actually materializing intermediate relations. The specific problem addressed here can be seen in that context or in the context of performing a web search, or a search in another large text database, for documents containing some or all of a set of keywords. For each keyword we are given the set of references to documents in which it occurs [2, 6, 9]. These sets are stored in some natural order, such as document date. In practice, the sets are large. For example, the average word from user query logs matches approximately a million documents on the AltaVista web search engine. Of course, one would hope that the answer to the query is small, particularly if the query is an intersection. It may also be expected that the elements of such an intersection are not spread uniformly through the initial
Influence of Environmental Conditions on Performance and Heart Rate Responses to the 30-15 Incremental Fitness Test in Rugby Union Athletes

Abstract Natera, AOW, Jennings, J, Oakley, AJ, and Jones, TW. Influence of environmental conditions on performance and heart rate responses to the 30-15 incremental fitness test in rugby union athletes. J Strength Cond Res 33(2): 486–491, 2019—The purpose of this study was to examine the differences in performance and heart rate (HR) responses between a high heat outdoor condition (34.0° C, 64.1% humidity) and a temperate indoor condition (22.0° C, 50.0% humidity) during the 30-15 intermittent fitness test (30-15IFT). Eight highly trained Rugby Union players (28.1 ± 1.5 years, 181.4 ± 8.8 cm, 88.4 ± 13.3 kg) completed the 30-15IFT in 2 different temperature conditions. Dependent variables recorded and analyzed included: final running speed of the 30-15IFT, HR at rest (HR rest), maximum HR (Max HR), HR recovery, average HR (HR ave), and submaximal HR corresponding to 25, 50, and 75% of final test speed (HR 25%, HR 50%, and HR 75%) and HR at 13 km·h−1 (HR 13 km·h−1). Greater running speeds were achieved when the test was conducted indoors (19.4 ± 0.7 km·h−1 vs. 18.6 ± 0.6 km·h−1, p = 0.002, d = 1.67). Average HR and HR 13 km·h−1 were greater when the test was conducted outdoors (p ⩽ 0.05, d > 0.85). Large effect sizes were observed for the greater HR at submaximal intensities (d > 0.90). The results of this study highlight the influence of temperature on 30-15IFT performance and cardiac responses. It is recommended that prescription of training based on 30-15IFT results reflects the temperature that the training will be performed in and that practitioners acknowledge that a meaningful change in assessment results can be the result of seasonal temperature change rather than training-induced change.
The Function of Conscious Experience: An Analogical Paradigm of Perception and Behavior

The question of whether conscious experience has any functional purpose depends on a more fundamental issue concerning the nature of conscious experience. In particular, whether the world of experience is the external world itself, as suggested by direct realism, or whether it is merely a virtualreality replica of that world in an internal representation, as in indirect realism, or representationalism. There is an epistemological problem with the notion of direct realism, for we cannot be consciously aware of objects beyond the sensory surface. Therefore the world of experience can only be an internal replica of the external world. This in turn validates a phenomenological approach to studying the nature of the perceptual representation in the brain. Phenomenology reveals that the representational strategy employed in the brain is an analogical one, in which objects are represented in the brain by constructing full spatial replicas of those objects in an internal representation.
Pittsburgh Compound B (11C-PIB) and Fluorodeoxyglucose (18 F-FDG) PET in Patients With Alzheimer Disease, Mild Cognitive Impairment, and Healthy Controls

Amyloid load in the brain using Pittsburgh compound B (11C-PIB) positron emission tomography (PET) and cerebral glucose metabolism using fluorodeoxyglucose (18F-FDG) PET were evaluated in patients with mild Alzheimer disease (AD, n = 18), mild cognitive impairment (MCI, n = 24), and controls (CTR, n = 18). 11C-PIB binding potential (BPND) was higher in prefrontal cortex, cingulate, parietal cortex, and precuneus in AD compared to CTR or MCI and in prefrontal cortex for MCI compared to CTR. For 18F-FDG, regional cerebral metabolic rate for glucose (rCMRGlu) was decreased in precuneus and parietal cortex in AD compared to CTR and MCI, with no MCI—CTR differences. For the AD—CTR comparison, precuneus BPND area under the receiver operating characteristic (ROC) curve (AUC) was 0.938 and parietal cortex rCMRGlu AUC was 0.915; for the combination, AUC was 0.989. 11C-PIB PET BPND clearly distinguished diagnostic groups and combined with 18F-FDG PET rCMRGlu, this effect was stronger. These PET techniques provide complementary information in strongly distinguishing diagnostic groups in cross-sectional comparisons that need testing in longitudinal studies.
The E.N.A.C.T. Model: Enhancing Teacher Candidates' Ability to Manage Student Behavior

This program description presents a model of critical reflection that has helped teacher candidates appropriately apply behavior management theory to resolve behavioral problems. The authors developed the ENACT (Examine, Name, Analyze, Critically evaluate, and Treat) model to help teacher candidates analyze the cause of inappropriate behaviors to resolve behavioral dilemmas in the classroom setting. A questionnaire supported that the model had an impact on teacher candidates' ability to manage chronic and troubling student behavior.
Bird Song Scene Analysis Using a Spatial-Cue-Based Probabilistic Model

This paper addresses bird song scene analysis based on semi-automatic annotation. Research in animal behavior, especially in birds, would be aided by automated or semi-automated systems that can localize sounds, measure their timing, and identify their sources. This is difficult to achieve in real environments, in which several birds at different locations may be singing at the same time. Analysis of recordings from the wild has usually required manual annotation. These annotations may be inaccurate or inconsistent, as they may vary within and between observers. Here we suggest a system that uses automated methods from robot audition, including sound source detection, localization, separation and identification. In robot audition, these technologies are assessed separately, but combining them has often led to poor performance in natural setting. We propose a new Spatial-Cue-Based Probabilistic Model (SCBPM) for their integration focusing on spatial information. A second problem has been that supervised machine learning methods usually require a pre-trained model, which may need a large training set of annotated labels. We have employed a semi-automatic annotation approach, in which a semi-supervised training method is deduced for a new model. This method requires much less pre-annotation. Preliminary experiments with recordings of bird songs from the wild revealed that our system outperformed the identification accuracy of a method based on conventional robot audition.1
DPY19L2 gene mutations are a major cause of globozoospermia: identification of three novel point mutations.

Globozoospermia, characterized by round-headed spermatozoa without acrosomes, is a rare and severe teratozoospermia causing primary male infertility. Homozygous DPY19L2 deletions have been identified as the main cause of globozoospermia, blocking sperm head elongation and acrosome formation. Several previous studies showed a very different prevalence of DPY19L2 gene deletions among globozoospermic patients in cohorts with different sample sizes and in different ethnic background. And all the patients previously analyzed were mainly of European, North African and Middle Eastern origins. So far, only 11 different point mutations of the DPY19L2 gene have been reported. To investigate the prevalence of DPY19L2 gene mutations in Chinese patients with globozoospermia and whether we can identify new sequence variants in this study, we recruited a total of 16 globozoospermic patients. Excluding one of two brothers, molecular analysis for deletions and mutations in the DPY19L2 gene was performed on 15 genetically independent individuals. Four of the 15 genetically independent patients with globozoospermia were homozygous for the DPY19L2 deletion, 5 were homozygous for a point mutation including a nucleotide deletion c.1532delA (two patients), a multi-mutation consisting of a nucleotide deletion c.1679delT and a two-nucleotide deletion c. 1681_1682delAC (c.[1679delT; 1681_1682delAC]) (one patient), a recurrent missense mutation R290H (one patient) and a missense mutation L330P (one patient). One additional patient had a heterozygous deletion in one allele but with no mutation identified in another allele. Overall, 60% of the patients (9/15) have a sequence variant of DPY19L2 in both alleles. This study confirms that the DPY19L2 mutations are the major cause of globozoospermia. Three novel point mutations and a recurrent missense mutation were found in this study, further broadening the spectrum of DPY19L2 mutations.
Predictive value of high-sensitivity troponin T in addition to EuroSCORE II in cardiac surgery.

OBJECTIVES Plasma troponins, measured by fourth-generation assays, are associated with increased mortality and morbidity after cardiac surgery. They also offer predictive information in addition to EuroSCORE, a widely used risk model after cardiac surgery. However, preoperatively measured troponin has provided no additional information to postoperative values. Whether these facts hold true also for the high-sensitivity fifth-generation troponin assay and the better calibrated risk model, EuroSCORE II, is unknown. We hypothesized that preoperative and/or postoperative high-sensitivity troponin T (hs-TnT) would increase the predictive value of EuroSCORE II. METHODS Consecutive coronary artery bypass grafting (CABG) and other cardiac surgical patients were prospectively enrolled in a university hospital. Plasma samples and EuroSCORE II variables were collected. The primary and secondary end-points were 180-day mortality and any major adverse event within 30 days, and 961-day mortality. The data were analysed by Kaplan-Meier survival curves, regression analyses, receiver operator characteristic curves and decision curve analysis. RESULTS Mortality rates in 180 days were 3.5% (15/428) in CABG and 6.4% (14/220) in other cardiac surgical patients. Survival curves differed only in patients with not only high postoperative hs-TnT value (>500 ng/l), but also high preoperative hs-TnT value (>14 ng/l), compared with patients with both hs-TnT values low. Adding hs-TnT to EuroSCORE II improved the prediction of 180-day mortality in other cardiac surgical patients (maximum net benefit of 1.5%), but not in CABG patients. Regarding major adverse events, adding hs-TnT to EuroSCORE II improved the prediction in both CABG patients and other cardiac surgical patients (maximum net benefits of 3 and 7%). CONCLUSIONS Elevated postoperative hs-TnT was predictive of mortality only when combined with elevated preoperative hs-TnT. Hs-TnT measurements added information to the EuroSCORE II regarding major adverse events in all cardiac surgical patients and regarding 180-day mortality in non-CABG patients.
Sifteo cubes

In this paper we describe Sifteo cubes™, a tangible and graphical user interface platform. We note several patterns of use observed in homes and schools and identify design recommendations for display utilization on distributed interfaces like Sifteo cubes. Additionally we discuss the process of commercializing the research prototype to create a marketable game system.
Kumamoto University Repository System Title Prognostic Nutritional Index Predicts Outcomes of Gastrectomy in the Elderly

Background: Owing to the increased life expectancy, elderly patients with gastric cancer is also increasing. Onodera’s prognostic nutritional index (PNI) is an assessment tool for nutritional status of surgical patients and possibly predicts prognosis of the patients. Aim of this study is to clarify the predictive and prognostic significance of PNI in elderly patients who underwent gastrectomy for gastric cancer. Methods: Two hundred ninety-five patients, including 196 nonelderly patients under 75 years old (Group NE) and 99 elderly patients (Group E), were eligible. We collected the data on nutritional status and the outcome of gastrectomy, including morbidity, mortality and survival of these patients. A Cox proportional hazards model was used to evaluate the prognostic significance. Results: PNI was significantly lower in E group than in NE group. Both morbidity and mortality rates after gastrectomy were similar between the groups. Although PNI could not predict the postoperative events in NE group, low PNI might be a risk of mortality and morbidity in the elderly. Although survival after gastrectomy was similar among groups divided by the median PNI value (49.2) in NE group, prognosis of PNI-L (<44.7) was significantly poorer than PNI-H (PNI≧44.7) in E group. Multivariate analysis demonstrated that PNI-L was an independent prognostic factor in the elderly. Conclusion: PNI predicts both short-term and long-term outcomes after
Predictors of Interest Group Lobbying Decisions

Both popular opinion and existing research suggest that money is the key predictor of interest group lobbying activity. However, this new research on interest group lobbying argues that the decision to spend money on lobbying is dependent on a range of resources, not just organizational wealth. Using a sample containing organizations that did and did not make lobbying expenditures in the 1998 election cycle, it shows how interest group resources explain differences in lobbying behavior among organizations with similar political goals. Despite the fact that both advocacy groups and labor unions seek electoral goals like getting new legislators into office, advocacy groups are less likely to spend money on lobbying than labor unions. In addition, firms are less likely to spend money on lobbying than trade associations, even though both types of groups primarily seek access to legislators. The availability of interest group resources, such as a committed membership and organizational experience, helps explain these differences in behavior. These findings suggest that fears about the corrupting influence of money on politics may be overstated.
MiniMuDS: A New Optimizer using Knowledge-Based Potentials Improves Scoring of Docking Solutions

In small molecule docking, the scoring and ranking of generated conformations is an important, though still not a completely resolved problem. Rescoring schemes often improve the quality of the obtained rankings. It is known that a local optimization is essential before a valid rescore value can be calculated. Here, we present a method that improves rescoring results obtained with the DrugScore function due to a new optimization technique. The method implements a more sophisticated search algorithm compared to the classic local optimization procedures used in this context. We validated the proposed method on a set of 192 protein-ligand complexes. Results show substantial improvements compared to original docking results with success rates increased by up to 10% for top scored solutions below 2 Å root-mean-square deviation to the native state and up to 18% increase below 1 Å, respectively.
Revisiting the complementarity between education and training – the role of job tasks and firm effects

This paper addresses the question to what extent the strong positive correlation between education and training can be attributed to differences in individual-, job- and firm-specific characteristics. The novelty of this paper is to analyze previously unconsidered characteristics, in particular, job tasks and firm-fixed effects. The results show that once job tasks are controlled for, the difference in training participation between educational groups drops considerably. In contrast, firm-fixed effects only play a minor role. Moreover, we show that workers performing nonroutine tasks are considerably more likely to participate in training than workers with routine tasks.
Multi-context cooperative coevolution in particle swarm optimization

A novel multi-context cooperatively coevolving particle swarm optimization (MCC-PSO) algorithm is proposed for the large-scale global optimization (LSGO) problems. As most optimization algorithms lose to find the global optimum on LSGO due to the curse of dimensionality, the famous cooperative co-evolution (CC) framework is proposed to overcome such weakness. In the basic CC framework, a single context vector is utilized for cooperatively but greedily coevolving different subcomponents, which sometimes loses its effectiveness. In this study, a novel multi-context cooperative coevolution framework and its application in PSO is proposed, in which more than one context vectors are employed to provide robust and effective co-evolution, as well as a new PSO updating rule based on the subpopulation in subcomponent (SPSC) structure and Gaussian distribution. On a comprehensive set of benchmarks (up to 1000 dimensionalities), the performance of MCC-PSO can rival several state-of-the-art evolutionary algorithms. Experimental results indicate that the novel multi-context CC framework is effective to improve the performance of PSO on LSGO and can be generally extended in other evolutionary algorithms.
Visual Programming of Plan Dynamics Using Constraints and Landmarks

In recent years, there has been considerable interest in the use of planning techniques in the area of new media. Many traditional planning notions no longer apply in the context of these applications. In particular, it can be difficult to answer the important question of what constitutes a good plan for the domain, but there is an emerging consensus that plan dynamics play an important role. As a consequence, it is important to support representation of such aspects. Our solution is to introduce a meta-level of representation that is an abstraction of the domain with respect to both time and causality, and to develop a visual representation of this in the form of a narrative arc. This visual representation can then be used in a visual programming approach to the exploration and specification of plan dynamics. In the paper we outline this approach to meta-level representation using constraints along with the visual programming interface we have developed. We illustrate the approach with examples of visual programming in the development of an interactive entertainment system based on Shakespeare's play ``The Merchant of Venice''
The role of HR actors in knowledge networks

Purpose – The paper aims to examine structural positions of individuals, especially HR actors (line managers and HR specialists) within relational networks for creating and sharing knowledge and to explore implications for designing and implementing HR practices in knowledge-intensive firms (KIF). Design/methodology/approach – This article used exploratory research design conducting a single case study of a KIF. Social network analysis (SNA) – network centrality measures and visualization tools – was used to examine the structural position of individuals. Findings – Line managers who are HR actors are centrally positioned within examined knowledge networks, while the HR specialist is not, which implies that the decentralized approach to HRM in KIF can be effective. Results also show that the more operational (instrumental) the information or knowledge flow is, the denser the knowledge networks. Research limitations/implications – This study provides support for devolution of HRM to the line in KIF. It suggests that HRM could affect the process of knowledge creation and sharing by implementing HR practices through centrally positioned line managers. A limitation of the research is a single case study and observed intensity rather than quality of relations. Practical implications – SNA appears to be an effective tool for mapping relationships in an organization. Centrally positioned HR actors (especially line managers involved in HRM) in knowledge networks are advantageous for HRM effectiveness only if obstacles to their effectiveness are properly managed. HR specialists should relate strongly to these actors to enable successful design and implementation of HR practices. Originality/value – The paper applies SNA to the HRM field, thus expanding the traditional view of HRM into examining the position of HR actors in relational networks and exploring their role in effectively executing HR practices.