Miracle-dz/UniFAR-FTUs huggingface dataset:
Southern ( SAIS ) 3-1-2004 Cultural Differences and Information Technology Acceptance

One of the main streams of research in the IS field is the explanation and prediction of Information technology (IT) adoption and usage. Even though several theories have been developed to address this phenomenon a consensus about the determinants of IT usage has emerged among researchers in the IS field. Specifically, the Technology Acceptance Model (TAM) (Davis, 1989) is considered to be the most parsimonious model in explaining IT use at the individual level. However, since individuals are conditioned by their culture, we propose to extend TAM such as we can understand the mechanism by which cultural differences could explain and predict behavior toward IT. Therefore, we integrate in our research model six cultural value-dimensions well established in the literature pertaining to comparative and cross-cultural management and showing a high variability between countries, which are “individualism/collectivism”, “power distance”, “masculinity/femininity”, “uncertainty avoidance” (Hofstede, 1997), “monochronic/polychromic time” (Trompenaars, Hampden-Turner, 1998, Hall, 1989) and “high context/low context”(Hall, 1989). A cross-sectional survey will be conducted in two subsidiaries of a multinational organization in two countries expected to be different enough in national cultural values. Questionnaires will be addressed to workers using the organizational e-mail system.
Pooled Analysis of Non-Union, Re-Operation, Infection, and Approach Related Complications after Anterior Odontoid Screw Fixation

Background Anterior odontoid screw fixation (AOSF) has been one of the most popular treatments for odontoid fractures. However, the true efficacy of AOSF remains unclear. In this study, we aimed to provide the pooled rates of non-union, reoperation, infection, and approach related complications after AOSF for odontoid fractures. Methods We searched studies that discussed complications after AOSF for type II or type III odontoid fractures. A proportion meta-analysis was done and potential sources of heterogeneity were explored by meta-regression analysis. Results Of 972 references initially identified, 63 were eligible for inclusion. 54 studies provided data regarding non-union. The pooled non-union rate was 10% (95% CI: 7%–3%). 48 citations provided re-operation information with a pooled proportion of 5% (95% CI: 3%–7%). Infection was described in 20 studies with an overall rate of 0.2% (95% CI: 0%–1.2%). The main approach related complication is postoperative dysphagia with a pooled rate of 10% (95% CI: 4%–17%). Proportions for the other approach related complications such as postoperative hoarseness (1.2%, 95% CI: 0%–3.7%), esophageal/retropharyngeal injury (0%, 95% CI: 0%–1.1%), wound hematomas (0.2%, 95% CI: 0%–1.8%), and spinal cord injury (0%, 95% CI: 0%–0.2%) were very low. Significant heterogeneities were detected when we combined the rates of non-union, re-operation, and dysphagia. Multivariate meta-regression analysis showed that old age was significantly predictive of non-union. Subgroup comparisons showed significant higher non-union rates in age ≥70 than that in age ≤40 and in age 40 to <50. Meta-regression analysis did not reveal any examined variables influencing the re-operation rate. Meta-regression analysis showed age had a significant effect on the dysphagia rate. Conclusions/Significances This study summarized the rates of non-union, reoperation, infection, and approach related complications after AOSF for odontoid factures. Elderly patients were more likely to experience non-union and dysphagia.
Dynamic Probabilistic Models for Latent Feature Propagation in Social Networks

Current Bayesian models for dynamic social network data have focused on modelling the influence of evolving unobserved structure on observed social interactions. However, an understanding of how observed social relationships from the past affect future unobserved structure in the network has been neglected. In this paper, we introduce a new probabilistic model for capturing this phenomenon, which we call latent feature propagation, in social networks. We demonstrate our model's capability for inferring such latent structure in varying types of social network datasets, and experimental studies show this structure achieves higher predictive performance on link prediction and forecasting tasks.
Concepts for Carbon Nanotube Sensors

This paper reports on concepts for carbon nanotube based sensors for mechanical and chemical quantities. We focus on single-walled carbon nanotubes as "simple" macro molecular functional structures with an option for integration in micro- and nanosystems or MEMS and NEMS and we discuss topics of relevance for fabrication. An extended reference list is included.
Concurrent performance of motor tasks and processing capacity in patients with schizophrenia

Any task is carried out more successfully if we allocate undivided attention to it, but as demands on attentional capacity increase—for example, in concurrent or dual task conditions—performance on attended tasks becomes more impaired. Patients with schizophrenia show impaired performance on tasks requiring high levels of attentional capacity. This study examines performance of 11 patients with schizophrenia and 13 normal controls on two motor tasks (placing pegs in a pegboard and repetitive index finger tapping) under unimanual, bimanual, and dual task conditions. The patients with schizophrenia placed fewer pegs and had reduced tapping speed in unimanual and bimanual conditions. However, the decrement in bimanual performance as a percentage of unimanual performance was not significantly different for the patients and controls on either the pegboard or tapping tasks. By contrast, under dual task conditions, the performance of the patients with schizophrenia in peg placement actually improved relative to the unimanual pegboard task, whereas tapping performance deteriorated compared with the unimanual tapping, a decrement that was significantly greater for the patients. Thus the improvement in the visually guided pegboard task was at the expense of the repetitive tapping task. These results are discussed in terms of an impairment of self initiated movement with general sparing of externally triggered movements in schizophrenia and the role of frontostriatal loops in this process.
Minimizing the set of local supervisors in fully decentralized supervision

A discrete-event system is controlled by a set of n local supervisors under decentralized supervision. Some local supervisors may be redundant in the sense that eliminating these local supervisors does not have an effect on the generated language. If the local supervisors are reliable, then we can reduce the cost of implementing supervisors by minimizing the set of local supervisors. Motivated by this, we present an algorithm to minimize the set of local supervisors by eliminating redundant ones in fully decentralized supervision proposed by Kozsk and Wonham (1990).
The Features and Functions of Neuronal Assemblies: Possible Dependency on Mechanisms beyond Synaptic Transmission

“Neuronal assemblies” are defined here as coalitions within the brain of millions of neurons extending in space up to 1–2 mm, and lasting for hundreds of milliseconds: as such they could potentially link bottom-up, micro-scale with top-down, macro-scale events. The perspective first compares the features in vitro versus in vivo of this underappreciated “meso-scale” level of brain processing, secondly considers the various diverse functions in which assemblies may play a pivotal part, and thirdly analyses whether the surprisingly spatially extensive and prolonged temporal properties of assemblies can be described exclusively in terms of classic synaptic transmission or whether additional, different types of signaling systems are likely to operate. Based on our own voltage-sensitive dye imaging (VSDI) data acquired in vitro we show how restriction to only one signaling process, i.e., synaptic transmission, is unlikely to be adequate for modeling the full profile of assemblies. Based on observations from VSDI with its protracted spatio-temporal scales, we suggest that two other, distinct processes are likely to play a significant role in assembly dynamics: “volume” transmission (the passive diffusion of diverse bioactive transmitters, hormones, and modulators), as well as electrotonic spread via gap junctions. We hypothesize that a combination of all three processes has the greatest potential for deriving a realistic model of assemblies and hence elucidating the various complex brain functions that they may mediate.
A LOCAL ADAPTIVE APPROACH FOR DENSE STEREO MATCHING IN ARCHITECTURAL SCENE RECONSTRUCTION

In recent years, a demand for 3D models of various scales and precisions has been growing for a wide range of applications; among them, cultural heritage recording is a particularly important and challenging field. We outline an automatic 3D reconstruction pipeline, mainly focusing on dense stereo-matching which relies on a hierarchical, local optimization scheme. Our matching framework consists of a combination of robust cost measures, extracted via an intuitive cost aggregation support area and set within a coarse-tofine strategy. The cost function is formulated by combining three individual costs: a cost computed on an extended census transformation of the images; the absolute difference cost, taking into account information from colour channels; and a cost based on the principal image derivatives. An efficient adaptive method of aggregating matching cost for each pixel is then applied, relying on linearly expanded cross skeleton support regions. Aggregated cost is smoothed via a 3D Gaussian function. Finally, a simple ‘winnertakes-all’ approach extracts the disparity value with minimum cost. This keeps algorithmic complexity and system computational requirements acceptably low for high resolution images (or real-time applications), when compared to complex matching functions of global formulations. The stereo algorithm adopts a hierarchical scheme to accommodate high-resolution images and complex scenes. In a last step, a robust post-processing work-flow is applied to enhance the disparity map and, consequently, the geometric quality of the reconstructed scene. Successful results from our implementation, which combines pre-existing algorithms and novel considerations, are presented and evaluated on the Middlebury platform.
Speaking "Up": A longitudinal corpus based on the "Up" film series

This report describes a speech corpus based on the “Up” series of documentary films by director Michael Apted, showing a set of individuals at seven year intervals over a period of 42 years. The broader goal of the research reported here is to analyze age-related change in speech across the adult life span. The corpus is based on portions of the films featuring the participants at ages 21 through 49. The current report describes the resulting database, which is freely available upon request to researchers, as well as some sample analyses of speaking rate and vowel formants. These analyses reveal subtle changes in each talker’s speaking rate and vowel spaces in the same direction as in previous studies investigating vocal aging, despite the much younger age range represented in this corpus.
3D facial expression recognition with geometrically localized facial features

This paper describes a pose invariant three-dimensional (3D) facial expression recognition method using distance vectors retrieved from 3D distributions of facial feature points to classify universal facial expressions. Probabilistic Neural Network architecture is employed as a classifier to recognize the facial expressions from a distance vector obtained from 3D facial feature locations. Facial expressions such as anger, sadness, surprise, joy, disgust, fear and neutral are successfully recognized with an average recognition rate of 87.8%.
Incidence and clinical significance of ESR1 mutations in heavily pretreated metastatic breast cancer patients

Background ESR1 mutation has recently emerged as one of the important mechanisms involved in endocrine resistance. The incidence and clinical implication of ESR1 mutation has not been well evaluated in heavily pretreated breast cancer patients. Methods We conducted a retrospective review of advanced breast cancer patients with tumors who underwent next-generation sequencing genomic profiling using Foundation One test at Cancer Treatment Centers of America® regional hospitals between November 2012 and November 2014. Results We identified a total of 341 patients including 217 (59%) estrogen receptor (ER)+, 177 (48%) progesterone receptor (PR)+, 30 (8%) hormone receptor+/HER2 positive, and 119 (32%) triple negative patients. ESR1 mutation was noted in 27/222 (12.1%) ER+ or PR+ breast cancer patients. All ER+ patients received at least one line of an aromatase inhibitor. All 28 patients were found to harbor ESR1 mutations affecting ligand-binding domain with the most common mutations affecting Y537 (17/28, 60.7%) and D538 (9/28, 32.1%). In this cohort, 19 (67.9%) patients carried three or more, seven (25%) patients had one or two additional genomic alterations and one (3.6%) patient had an ESR1 mutation only. Of 28 patients, three patients were treated with fulvestrant immediately before and two patients were treated after next-generation sequencing testing; only one patient achieved stable disease for 8 months and the other four patients had progression of disease. In all, 3/3 (100%) patients before testing and 2/4 (50%) after testing treated with exemestane and everolimus achieved stable disease for at least 6 months. Conclusion ESR1 mutation was found in 12.1% of a large cohort of advanced breast cancer patients. Exemestane in combination with everolimus might be a reasonable option. Prospective studies are warranted to validate these findings.
Understanding Students’ Explanations in Geometry Tutoring

Precise Natural Language Understanding is needed in Geometry Tutoring to accurately determine the semantic content of students' explanations. The paper presents an NLU system developed in the context of the Geometry Explanation Tutor. The system combines unification-based syntactic processing with description logics based semantics to achieve the necessary accuracy level. Solutions to specific semantic problems dealing with equivalence of semantic representations are described. Experimental results on classification accuracy are also presented.
Long-Term Exposure to Ambient Air Pollution and Incidence of Postmenopausal Breast Cancer in 15 European Cohorts within the ESCAPE Project

Background: Epidemiological evidence on the association between ambient air pollution and breast cancer risk is inconsistent. Objective: We examined the association between long-term exposure to ambient air pollution and incidence of postmenopausal breast cancer in European women. Methods: In 15 cohorts from nine European countries, individual estimates of air pollution levels at the residence were estimated by standardized land-use regression models developed within the European Study of Cohorts for Air Pollution Effects (ESCAPE) and Transport related Air Pollution and Health impacts - Integrated Methodologies for Assessing Particulate Matter (TRANSPHORM) projects: particulate matter (PM) ≤2.5μm, ≤10μm, and 2.5–10μm in diameter (PM2.5, PM10, and PMcoarse, respectively); PM2.5 absorbance; nitrogen oxides (NO2 and NOx); traffic intensity; and elemental composition of PM. We estimated cohort-specific associations between breast cancer and air pollutants using Cox regression models, adjusting for major lifestyle risk factors, and pooled cohort-specific estimates using random-effects meta-analyses. Results: Of 74,750 postmenopausal women included in the study, 3,612 developed breast cancer during 991,353 person-years of follow-up. We found positive and statistically insignificant associations between breast cancer and PM2.5 {hazard ratio (HR)=1.08 [95% confidence interval (CI): 0.77, 1.51] per 5 μg/m3}, PM10 [1.07 (95% CI: 0.89, 1.30) per 10 μg/m3], PMcoarse [1.20 (95% CI: 0.96, 1.49 per 5 μg/m3], and NO2 [1.02 (95% CI: 0.98, 1.07 per 10 μg/m3], and a statistically significant association with NOx [1.04 (95% CI: 1.00, 1.08) per 20 μg/m3, p=0.04]. Conclusions: We found suggestive evidence of an association between ambient air pollution and incidence of postmenopausal breast cancer in European women. https://doi.org/10.1289/EHP1742
Theophylline: a review of population pharmacokinetic analyses

Numerous population pharmacokinetic studies of theophylline have been conducted in paediatric and adult patients. The purpose of this review was to summarize the published studies concerning population pharmacokinetics of theophylline in patients of different ages and discuss factors that might cause the large variability in the pharmacokinetics of theophylline.
Efficient approximation of Sparse Jacobians for time‐implicit reduced order models

This paper introduces a sparse matrix discrete interpolation method to effectively compute matrix approximations in the reduced order modeling framework. The sparse algorithm developed herein relies on the discrete empirical interpolation method and uses only samples of the nonzero entries of the matrix series. The proposed approach can approximate very large matrices, unlike the current matrix discrete empirical interpolation method, which is limited by its large computational memory requirements. The empirical interpolation indices obtained by the sparse algorithm slightly differ from the ones computed by the matrix discrete empirical interpolation method as a consequence of the singular vectors round‐off errors introduced by the economy or full singular value decomposition (SVD) algorithms when applied to the full matrix snapshots. When appropriately padded with zeros, the economy SVD factorization of the nonzero elements of the snapshots matrix is a valid economy SVD for the full snapshots matrix. Numerical experiments are performed with the 1D Burgers and 2D shallow water equations test problems where the quadratic reduced nonlinearities are computed via tensorial calculus. The sparse matrix approximation strategy is compared against five existing methods for computing reduced Jacobians: (i) matrix discrete empirical interpolation method, (ii) discrete empirical interpolation method, (iii) tensorial calculus, (iv) full Jacobian projection onto the reduced basis subspace, and (v) directional derivatives of the model along the reduced basis functions. The sparse matrix method outperforms all other algorithms. The use of traditional matrix discrete empirical interpolation method is not possible for very large dimensions because of its excessive memory requirements. Copyright © 2016 John Wiley & Sons, Ltd.
A new type of intrusion prevention system

In order to strengthen network security and improve the network's active defense intrusion detection capabilities, this paper presented and established one active defense intrusion detection system which based on the mixed interactive honeypot. The system can help to reduce the false information, enhance the stability and security of the network. Testing and simulation experiments show that: the system improved active defense of the network's security, increase the honeypot decoy capability and strengthen the attack predictive ability. So it has better application and promotion value.
Genetic Diversity Among Simian Immunodeficiency Virus Isolates From African Green Monkeys

To characterize isolates further within the SIVagm subtype, we studied four SIVagm isolates by cross‐hybridization, molecular cloning, and nucleotide sequencing. Our results indicate an unexpected degree of genetic variation among isolates within the SIVagm subtype comparable to the variation between SIVmac and HIV‐2.
On‐line inference for multiple changepoint problems

Summary. We propose an on‐line algorithm for exact filtering of multiple changepoint problems. This algorithm enables simulation from the true joint posterior distribution of the number and position of the changepoints for a class of changepoint models. The computational cost of this exact algorithm is quadratic in the number of observations. We further show how resampling ideas from particle filters can be used to reduce the computational cost to linear in the number of observations, at the expense of introducing small errors, and we propose two new, optimum resampling algorithms for this problem. One, a version of rejection control, allows the particle filter to choose the number of particles that are required at each time step automatically. The new resampling algorithms substantially outperform standard resampling algorithms on examples that we consider; and we demonstrate how the resulting particle filter is practicable for segmentation of human G+C content.
Growing an organic indoor location system

Most current methods for 802.11-based indoor localization depend on surveys conducted by experts or skilled technicians. Some recent systems have incorporated surveying by users. Structuring localization systems "organically," however, introduces its own set of challenges: conveying uncertainty, determining when user input is actually required, and discounting erroneous and stale data. Through deployment of an organic location system in our nine-story building, which contains nearly 1,400 distinct spaces, we evaluate new algorithms for addressing these challenges. We describe the use of Voronoi regions for conveying uncertainty and reasoning about gaps in coverage, and a clustering method for identifying potentially erroneous user data. Our algorithms facilitate rapid coverage while maintaining positioning accuracy comparable to that achievable with survey-driven indoor deployments.
Towards an objective assessment of alzheimer's disease: the application of a novel evolutionary algorithm in the analysis of figure copying tasks

Alzheimer's is a chronic debilitating neurodegenerative disease that is difficult to diagnose; conventional approaches are subjective and can be unreliable. This paper describes work towards an objective assessment that uses an evolutionary algorithm to assess an important symptom of the disease, the loss of visuo-spatial ability. Results are presented for application of the system in assessing the immature visuo-spatial ability of 7-11 year old children, which are used as a model for Alzheimer's disease patients.
Outage Performance for Cooperative NOMA Transmission with an AF Relay

This letter studies the outage performance of cooperative non-orthogonal multiple access (NOMA) network by adopting an amplify-and-forward relay. An accurate approximation for the outage probability is derived and then the asymptotic behaviors are investigated. It is revealed that cooperative NOMA achieves the same diversity order and the superior coding gain compared to cooperative orthogonal multiple access. It is also shown that the outage performance improves when the distance between the relay and indirect link user decreases, assuming the smaller transmit power of relay than the base station.
A Hypergraph Approach to the Identifying Parent Property: The Case of Multiple Parents

Let C be a code of length n over an alphabet of q letters. A word y is called a descendant of a set of t codewords x1,…,xt if yie{xi1,…,xit} for all i=1,…,n. A code is said to have the identifiable parent property if for any n-word that is a descendant of at most t parents it is possible to identify at least one of them. We prove that for any t <= q−1 there exist sequences of such codes with asymptotically nonvanishing rate.