Miracle-dz/UniFAR-FTUs huggingface dataset:
The overuse of self-report in the study of beliefs in education: epistemological considerations

ABSTRACT The last few decades abound in studies concerned with what teachers, students, parents, and other participants in the educational process believe about a wide variety of issues. Most of these studies follow methodological procedures based on reports that people make about their own beliefs. We argue that this strategy is seriously flawed under certain conditions that often obtain and, therefore, we should revise what we know so far about people’s beliefs. We also suggest a more suitable alternative procedure.
Chemical extractives of the tropical wood Wallaba are natural anti-swelling agents

1 Wallaba ( Eperua falcata ) is a tropical wood which is known to have naturally low swelling 2 characteristics. Samples of wallaba heartwood were subjected to differential solvent 3 extraction. Wood pieces that were extracted with methanol experienced significantly higher 4 swelling after rehydration from oven dry to 96% relative humidity in comparison to non- 5 extracted samples and samples extracted with other solvents. Methanol soluble wallaba 6 heartwood extract was purified by high pressure liquid chromatography and the compounds 7 present were characterised by nuclear magnetic resonance spectroscopy. Methanol extract was 8 found to contain a very high relative proportion of polar compounds which are proposed to 9 bind to the polymeric cell wall by multiple hydrogen bonds restricting the association of water 10 and therefore acting as natural anti-swelling agents. 11
Turbo Decoding as an Approximative Iterative Solution to Maximum Likelihood Sequence Detection

Despite the considerable research effort towards the analysis and understanding of the nature of turbo decoding, a clear identification of the underlying optimization problem the turbo decoder attempts to solve is still missing. In this paper, we link the turbo decoding algorithm to maximum likelihood (ML) sequence detection by demonstrating how the turbo decoder can be systematically derived starting from the ML sequence detection criterion. In particular, we show that a method to solve the ML sequence detection problem is to iteratively solve the corresponding critical point equations of an equivalent unconstrained estimation problem by means of fixed-point iterations. The turbo decoding algorithm is obtained by approximating the overall a posteriori probabilities, such that the fixed-point iteration becomes feasible and the optimum ML solution is still a solution of the corresponding approximate critical point equations.
Utilizing social network analysis in social sciences in sport

Abstract In recent years, a constantly increasing trend towards attempts at exploring relational attributes through social network analysis has been observed, shifting away from conventional individualistic attributes. A big advantage of social network analysis lies in the visualization of subjects’ interactions and relational patterns and the resulting emergence phenomenon. The current study introduces essential concepts and theories of social network analysis in an aim to illuminate how it might be used to investigate individual and group behaviours in the field of sport social science research. Social network analysis has not yet been popularized in social science in sport research in comparison with its relatively wide adoption in other social sciences. In social science in sport, social network analysis can be used in various research areas such as social networks and knowledge networks, and it can lead exploration of previously unexplored research areas.
Population-Based Input Function Modeling for [18F]FMPEP-d 2, an Inverse Agonist Radioligand for Cannabinoid CB1 Receptors: Validation in Clinical Studies

Background Population-based input function (PBIF) may be a valid alternative to full blood sampling for quantitative PET imaging. PBIF is typically validated by comparing its quantification results with those obtained via arterial sampling. However, for PBIF to be employed in actual clinical research studies, its ability to faithfully capture the whole spectrum of results must be assessed. The present study validated a PBIF for [18F]FMPEP-d 2, a cannabinoid CB1 receptor radioligand, in healthy volunteers, and also attempted to utilize PBIF to replicate three previously published clinical studies in which the input function was acquired with arterial sampling. Methods The PBIF was first created and validated with data from 42 healthy volunteers. This PBIF was used to assess the retest variability of [18F]FMPEP-d 2, and then to quantify CB1 receptors in alcoholic patients (n = 18) and chronic daily cannabis smokers (n = 29). Both groups were scanned at baseline and after 2–4 weeks of monitored drug abstinence. Results PBIF yielded accurate results in the 42 healthy subjects (average Logan-distribution volume (V T) was 13.3±3.8 mL/cm3 for full sampling and 13.2±3.8 mL/cm3 for PBIF; R2 = 0.8765, p<0.0001) and test-retest results were comparable to those obtained with full sampling (variability: 16%; intraclass correlation coefficient: 0.89). PBIF accurately replicated the alcoholism study, showing a widespread ∼20% reduction of CB1 receptors in alcoholic subjects, without significant change after abstinence. However, a small PBIF-V T bias of −9% was unexpectedly observed in cannabis smokers. This bias led to substantial errors, including a V T decrease in regions that had shown no downregulation in the full input function. Simulated data showed that the original findings could only have been replicated with a PBIF bias between −6% and +4%. Conclusions Despite being initially well validated in healthy subjects, PBIF may misrepresent clinical protocol results and be a source of variability between different studies and institutions.
Research for a Dynamic Recurrent Fuzzy Wavelet Network

This paper proposes a dynamic recurrent fuzzy wavelet network (DRFWN) for identified nonlinear dynamic systems. Temporary relations are embedded in the network by adding feedback connections in the second layer of the fuzzy wavelet network. In addition, the study algorithm of the DRFWN is introduced and its stability analysis is studied. Finally, the DRFWN is applied in several simulations. The results verify the effectiveness of the DRFWN
Comparative Physiological and Proteomic Analyses of Poplar (Populus yunnanensis) Plantlets Exposed to High Temperature and Drought

Plantlets of Populus yunnanensis Dode were examined in a greenhouse for 48 h to analyze their physiological and proteomic responses to sustained heat, drought, and combined heat and drought. Compared with the application of a single stress, simultaneous treatment with both stresses damaged the plantlets more heavily. The plantlets experienced two apparent response stages under sustained heat and drought. During the first stage, malondialdehyde and reactive oxygen species (ROS) contents were induced by heat, but many protective substances, including antioxidant enzymes, proline, abscisic acid (ABA), dehydrin, and small heat shock proteins (sHSPs), were also stimulated. The plants thus actively defended themselves against stress and exhibited few pathological morphological features, most likely because a new cellular homeostasis was established through the collaborative operation of physiological and proteomic responses. During the second stage, ROS homeostasis was overwhelmed by substantial ROS production and a sharp decline in antioxidant enzyme activities, while the synthesis of some protective elements, such as proline and ABA, was suppressed. As a result, photosynthetic levels in P. yunnanensis decreased sharply and buds began to die, despite continued accumulation of sHSPs and dehydrin. This study supplies important information about the effects of extreme abiotic environments on woody plants.
Rule-base technique for component adaptation to support QoS-based reconfiguration

Many critical application systems require reconfigurability in order to adapt under changing environment. To achieve system reconfigurability, it is possible to use adaptation mechanisms that are external to components or to use parameterized components. This paper focuses on making components reconfigurable in terms of QoS tradeoffs. We propose a new component parameterization technique which can transform individual components to reconfigurable ones such that they can support various QoS tradeoffs to achieve overall system QoS requirements. The parameterized components can be used to develop both statically and dynamically reconfigurable systems. The proposed technique is rule based, which provides flexibility and extensibility to enhance and improve the technique. A tool set has been developed based on the proposed technique to achieve semi-automated component parameterization.
fast_protein_cluster: parallel and optimized clustering of large-scale protein modeling data

Motivation: fast_protein_cluster is a fast, parallel and memory efficient package used to cluster 60 000 sets of protein models (with up to 550 000 models per set) generated by the Nutritious Rice for the World project. Results: fast_protein_cluster is an optimized and extensible toolkit that supports Root Mean Square Deviation after optimal superposition (RMSD) and Template Modeling score (TM-score) as metrics. RMSD calculations using a laptop CPU are 60× faster than qcprot and 3× faster than current graphics processing unit (GPU) implementations. New GPU code further increases the speed of RMSD and TM-score calculations. fast_protein_cluster provides novel k-means and hierarchical clustering methods that are up to 250× and 2000× faster, respectively, than Clusco, and identify significantly more accurate models than Spicker and Clusco. Availability and implementation: fast_protein_cluster is written in C++ using OpenMP for multi-threading support. Custom streaming Single Instruction Multiple Data (SIMD) extensions and advanced vector extension intrinsics code accelerate CPU calculations, and OpenCL kernels support AMD and Nvidia GPUs. fast_protein_cluster is available under the M.I. T. license. (http://software.compbio.washington.edu/fast_protein_cluster) Contact: lhhung@compbio.washington.edu Supplementary information: Supplementary data are available at Bioinformatics online.
Evolutionary Clustering and Analysis of User Behaviour in Online Forums

In this paper we cluster and analyse temporal user behaviour in online communities. We adapt a simple unsupervised clustering algorithm to an evolutionary setting where we cluster users into prototypical behavioural roles based on features derived from their ego-centric reply-graphs. We then analyse changes in the role membership of the users over time, the change in role composition of forums over time and examine the differences between forums in terms of role composition. We perform this analysis on 200 forums from a popular national bulletin board and 14 enterprise technical support forums.
A rigorous and realistic Shape From Shading method and some of its applications

This article proposes a rigorous and realistic solution of the Lambertian Shape From Shading (SFS) problem. The power of our approach is threefolds. First, our work is based on a rigorous mathematical method: we define a new notion of weak solutions (in the viscosity sense) which does not necessarily requires boundary data (contrary to the work of [rouy-tourin:92,prados-faugeras-etal:02,prados-faugeras:03,camilli-falcone:96,falcone-sagona-etal:01]) and which allows to define a solution as soon as the image is (Lipschitz) continuous (contrary to the work of [oliensis:91,dupuis-oliensis:94]). We prove the existence and uniqueness of this (new) solution and we approximate it by using a provably convergent algorithm. Second, it improves the applicability of the SFS to real images: we complete the realistic work of [prados-faugeras:03,tankus-sochen-etal:03], by modeling the problem with a pinhole camera and with a single point light source located at the optical center. This new modelization appears very relevant for applications. Moreover, our algorithm can deal with images containing discontinuities and black shadows. It is very robust to pixel noise and to errors on parameters. It is also generic: i.e. we propose a unique algorithm which can compute numerical solutions of the various perspective and orthographic SFS models. Finally, our algorithm seems to be the most efficient iterative algorithm of the SFS literature. Third, we propose three applications (in three different areas) based on our SFS method.
PATS: Realization and user evaluation of an automatic playlist generator

A means to ease selecting preferred music referred to as Personalized Automatic Track Selection (PATS) has been developed. PATS generates playlists that suit a particular context-of-use, that is, the real-world environment in which the music is heard. To create playlists, it uses a dynamic clustering method in which songs are grouped based on their attribute similarity. The similarity measure selectively weighs attribute-values, as not all attribute-values are equally important in a context-of-use. An inductive learning algorithm is used to reveal the most important attribute-values for a context-of-use from preference feedback of the user. In a controlled user experiment, the quality of PATS-compiled and randomly assembled playlists for jazz music was assessed in two contexts-of-use. The quality of the randomly assembled playlists was used as base-line. The two contexts-of-use were (cid:145)listening to soft music(cid:146) and (cid:145)listening to lively music(cid:146). Playlist quality was measured by precision (songs that suit the context-of-use), coverage (songs that suit the context-of-use but that were not already contained in previous playlists) and a rating score . Results showed that PATS playlists contained increasingly more preferred music (increasingly higher precision ), covered more preferred music in the collection (higher coverage ), and were rated higher than randomly assembled playlists.
The Sexual Violence Risk-20: factor structure and psychometric properties

Abstract Although the Sexual Violence Risk-20 (SVR-20) is widely used, its psychometric properties have only been investigated in a limited number of studies. This study explored the factor structure of the SVR-20 and examined its psychometric properties. Confirmatory factor analysis (CFA) was used to examine the fit of the original three-domain model of the SVR-20. The CFA showed that the original structure was not satisfactory. Exploratory principal components analysis (PCA) was conducted in search of a more optimal factor structure. Psychometric properties (i.e., internal consistency, predictive value, and convergent validity) of both the original domains and alternative factors were investigated. The PCA and subsequent CFAs pointed in the direction of an alternative, more optimal three-factor solution. The three alternative factors were labeled as Antisociality, Sexual deviance, and Problematic thinking and produced better internal consistency coefficients than the original domains. However, the validity of the SVR-20 was modest and no evidence was found indicating that the alternative factors were better in this regard as compared to the original domains. Despite the overall superiority of actuarial measures in predicting recidivism, the structured professional judgment of the SVR-20 proved to be more predictive of sexual, violent, and general recidivism than its actuarial scoring method.
Objective Function Design for MCE-Based Combination of On-line and Off-line Character Recognizers for On-line Handwritten Japanese Text Recognition

This paper describes effective object function design for combining on-line and off-line character recognizers for on-line handwritten Japanese text recognition. We combine on-line and off-line recognizers using a linear or nonlinear function with weighting parameters optimized by the MCE criterion. We apply a k-means method to cluster the parameters of all character categories into groups so that the categories belonging to the same group have the same weight parameters. Moreover, we apply a genetic algorithm to estimate super parameters such as the number of clusters, initial learning rate and maximum learning times as well as the sigmoid function parameter for MCE optimization. Experimental results on horizontal text lines extracted from the TUAT Kondate database demonstrate the superiority of our method.
The obligated bystander: An analysis of factors which influence teacher intervention in school bullying

vi CHAPTER 1 TEACHERS AS BYSTANDERS IN SCHOOL BULLYING . 1 Background to the Problem . 2 Statement of the Problem . 4 Purpose of the Study . 4 Research Questions . 4 Significance of the Problem . 5 Methodology . 6 Assumptions . 7 Limitations . 7 Delimitations . 8 Definition of Terms . 8 Organization of the Study . 9 CHAPTER 2 REVIEW OF THE LITERATURE . 11 Bullying . 12 Anti-Bullying Policies . 13 Student Experience with Bullying . 14 Teacher Experience with Bullying . 17 Bystander Intervention . 35 Conclusions . 45 Implications. 46
An opportunistic channel access scheme for interweave cognitive radio systems

We propose a novel opportunistic access scheme for cognitive radios in an interweave cognitive system, that considers the channel gain as well as the predicted idle channel probability (primary user occupancy: Busy/idle). In contrast to previous work where a cognitive user vacates a channel only when that channel becomes busy, the proposed scheme requires the cognitive user to switch to the channel with the next highest idle probability if the current channel's gain is below a certain threshold. We derive the threshold values that maximize the long term throughput for various primary user transition probabilities and cognitive user's relative movement.
A novel iris database indexing method using the iris color

In a very large iris database, the design of an effective iris indexing method reduces the computational complexity of feature matching process. This paper presents a new iris indexing technique based on the iris color for noisy iris images. The proposed method using the chrominance components achieves high indexing performance in defocused, reflection-contained and eyelid-occluded iris images. The performance measures such as the hit rate and the penetration rate computed on a recently created noisy iris database, namely UBIRIS (Proenca and Alexandre, 2005), show the effectiveness of the iris color to index very large iris databases.
Feasibility of Real-Time Satisfaction Surveys Through Automated Analysis of Patients' Unstructured Comments and Sentiments

This article shows how sentiment analysis (an artificial intelligence procedure that classifies opinions expressed within the text) can be used to design real-time satisfaction surveys. To improve participation, real-time surveys must be radically short. The shortest possible survey is a comment card. Patients' comments can be found online at sites organized for rating clinical care, within e-mails, in hospital complaint registries, or through simplified satisfaction surveys such as “Minute Survey. ” Sentiment analysis uses patterns among words to classify a comment into a complaint, or praise. It further classifies complaints into specific reasons for dissatisfaction, similar to broad categories found in longer surveys such as Consumer Assessment of Healthcare Providers and Systems. In this manner, sentiment analysis allows one to re-create responses to longer satisfaction surveys from a list of comments. To demonstrate, this article provides an analysis of sentiments expressed in 995 online comments made at the RateMDs.com Web site. We focused on pediatrician and obstetrician/gynecologist physicians in District of Columbia, Maryland, and Virginia. We were able to classify patients' reasons for dissatisfaction and the analysis provided information on how practices can improve their care. This article reports the accuracy of classifications of comments. Accuracy will improve as the number of comments received increases. In addition, we ranked physicians using the concept of time-to-next complaint. A time-between control chart was used to assess whether time-to-next complaint exceeded historical patterns and therefore suggested a departure from norms. These findings suggest that (1) patients' comments are easily available, (2) sentiment analysis can classify these comments into complaints/praise, and (3) time-to-next complaint can turn these classifications into numerical benchmarks that can trace impact of improvements over time. The procedures described in the article show that real-time satisfaction surveys are possible.
Equilibrium Wage Dispersion with Worker and Employer Heterogeneity

We construct and estimate an equilibrium search model with on–the–job–search. Firms make take–it–or–leave–it wage offers to workers conditional on their characteristics and they can respond to the outside job offers received by their employees. Unobserved worker productive heterogeneity is introduced in the form of cross–worker differences in a "competence" parameter. On the other side of the market, firms also are heterogeneous with respect to their marginal productivity of labor. The model delivers a theory of steady–state wage dispersion driven by heterogenous worker abilities and firm productivities, as well as by matching frictions. The structural model is estimated using matched employer and employee French panel data. The exogenous distributions of worker and firm heterogeneity components are nonparametrically estimated. We use this structural estimation to provide a decomposition of cross–employee wage variance. We find that the share of the cross–sectional wage variance that is explained by person effects varies across skill groups. Specifically, this share lies close to 40% for high–skilled white collars, and quickly decreases to 0% as the observed skill level decreases. The contribution of market imperfections to wage dispersion is typically around 50%
Induction of apoptosis and autophagy via mitochondria- and PI3K/Akt/mTOR-mediated pathways by E. adenophorum in hepatocytes of saanen goat

E. adenophorum has reported to cause hepatotoxicity. But, the precise effects of E. adenophorum on hepatocytes is unclear. Saanen goats were fed on E. adenophorum to detect the cytotoxicity effects of E. adenophorum on hepatocytes. Our study has shown that the typical apoptotic features, the increasing apoptotic hepatocytes and activated caspase-9, −3 and the subsequent cleavage of PARP indicated the potent pro-apoptotic effects of E. adenophorum. Moreover, the translocation of Bax and Cyt c between mitochondria and cytosol triggering the forming of apoptosome proved that the mitochondria-mediated apoptosis was triggered by E. adenophorum. Furthermore, E. adenophorum increased the MDC-positive autophagic vacuoles and the subcellular localization of punctate LC3, the ratio of LC3-II/LC3-I and the protein levels of Beclin 1, but decreased that of P62, indicating the potent pro-autophagic effects of E. adenophorum. In addition, E. adenophorum significantly inhibited the protein leves of p-PI3K, p-Akt and p-mTORC1, but increased PTEN and p-AMPK. Also, the p-mTORC2 and p-Akt Ser473 were inhibited, indicating that the supression of mTORC2/Akt pathway could induce the autophagy of hepatocytes. The autophagy-realted results indicated that the inhibition of PI3K/Akt/mTORC1- and mTORC2/Akt-mediated pathways contributed to the pro-autophagic activity of E. adenophorum. These findings provide new insights to understand the mechanisms involved in E. adenophorum-caused hepatotoxicity of Saanen goat.
A Review of Auditory Perceptual Theories and the Prospects for an Ecological Account

Contents 1 Introduction 1 1.1 Motivation 1 1.2 Definitions 1 1.3 The neglect of auditory perceptual theory 2 2 Opinions on the role of auditory perception 4 2.1 Opinions on the role of perception in general 4 2.2 The role of hearing according to Helmholtz 5 2.3 The role of hearing according to James 7 2.4 The role of hearing according to Gibson 7 2.5 Other opinions: identification or source recovery? 8 2.6 Summary 9 3 Theories of Auditory Perception 9 3.