Miracle-dz/UniFAR-FTUs huggingface dataset:
Constructing a Chinese valence-arousal dictionary with multiple heterogeneous lexicons

This paper proposed an approach to estimate the DSAW-defined valence of words. The valence is converted from sentimental polarity and strength of each word in the CSWN, according to the training data provided by DSAW. In addition, this paper also proposed a method to estimate the arousal for each word based on an observation: increasingly more positive and negative sentiments suggest a stronger arousal. Experimental results show that there is no considerable difference in the prediction results between the methods proposed by this study and other methods. To build a sentiment lexicon under the lack of language tools or resources, the methods proposed in this study may be some of the options for solving the problems.
The Secondary-Tertiary Transition in Mathematics: What High School Teachers Do to Prepare Students for Future Success in College-Level Calculus

Quantitative analysis of the Factors Influencing College Success in Mathematics (FICSMath) Survey data indicates that high school mathematics teachers’ abilities to teach for conceptual understanding is a significant and positive predictor of student performance in single- variable college calculus. To explore these findings further, we gathered and analyzed interview data gained from a representative sample of high school precalculus teachers from across the U.S., identified by their students as requiring high levels of conceptual understanding (n = 13). Seventeen themes were identified and then combined into five overarching phenomenological themes. These overarching themes suggest that teachers who teach for high conceptual understanding (a) support relational understanding during problem solving, (b) require students to learn how to study to build on prior knowledge and learn from mistakes, (c) use mathematical language and ask critical questions to support learning, (d) focus on content knowledge necessary to make connections, and (e) use technology to support learning concepts but limit calculator use. Comparison of these results to quantitative findings further illuminate that intentional development of disciplinary knowledge, cognition, and language are noteworthy points of intersection for teachers and researchers alike.
Single Document Summarization Based on Local Topic Identification and Word Frequency

In this task, an approach for single document summaries based on local topic identification and word frequency is proposed. In recent years, there has been increased interest in automatic summarization. The physical features are often used and have been successfully applied to this field; it also has some disadvantages of non-redundancy, structure and coherence. Therefore, we introduced logical structure feature which has been successfully applied in multi-document summarization (MDS), and we designed a system to accomplish this task. Documents can be clustered into local topic after sentences similarity is calculated, which can be sorted by the scoring. Then sentences from all local topics are selected by computing the word frequency. Using this proposed method, the information redundancy of each local topic and among local topic is reduced. The information coverage ratio and structure of the summarization is improved.
3D Finger CAPE: Clicking Action and Position Estimation under Self-Occlusions in Egocentric Viewpoint

In this paper we present a novel framework for simultaneous detection of click action and estimation of occluded fingertip positions from egocentric viewed single-depth image sequences. For the detection and estimation, a novel probabilistic inference based on knowledge priors of clicking motion and clicked position is presented. Based on the detection and estimation results, we were able to achieve a fine resolution level of a bare hand-based interaction with virtual objects in egocentric viewpoint. Our contributions include: (i) a rotation and translation invariant finger clicking action and position estimation using the combination of 2D image-based fingertip detection with 3D hand posture estimation in egocentric viewpoint. (ii) a novel spatio-temporal random forest, which performs the detection and estimation efficiently in a single framework. We also present (iii) a selection process utilizing the proposed clicking action detection and position estimation in an arm reachable AR/VR space, which does not require any additional device. Experimental results show that the proposed method delivers promising performance under frequent self-occlusions in the process of selecting objects in AR/VR space whilst wearing an egocentric-depth camera-attached HMD.
Dealing With Software Concerns In Aspects

The actual realization of a design language form has been revealed to be non-trivial. Most of the design languages are very much tailored towards a specific application or application domain. Moreover, with the exception of very few hardly any of these language notations have been used outside their own research environment. The development of a more generic aspect oriented design language requires a wider and more thorough look at the requirements. This paper examines the design notation issues and discusses how it fulfils the requirements in principle and design and consequently would lead to a general purpose AOSD design language (AOSDDL) that will map AOSD design notations to the existing AOP languages.
Level Set Estimation from Projection Measurements: Performance Guarantees and Fast Computation

Estimation of the level set of a function (i.e., regions where the function exceeds some value) is an important problem with applications in digital elevation mapping, medical imaging, astronomy, etc. In many applications, the function of interest is not observed directly. Rather, it is acquired through (linear) projection measurements, such as tomographic projections, interferometric measurements, coded-aperture measurements, and random projections associated with compressed sensing. This paper describes a new methodology for rapid and accurate estimation of the level set from such projection measurements. The key defining characteristic of the proposed method, called the projective level set estimator, is its ability to estimate the level set from projection measurements without an intermediate reconstruction step. This leads to significantly faster computation relative to heuristic “plug-in" methods that first estimate the function, typically with an iterative algorithm, and then threshold the result.
Bilinear Programming for Human Activity Recognition with Unknown MRF Graphs

Markov Random Fields (MRFs) have been successfully applied to human activity modelling, largely due to their ability to model complex dependencies and deal with local uncertainty. However, the underlying graph structure is often manually specified, or automatically constructed by heuristics. We show, instead, that learning an MRF graph and performing MAP inference can be achieved simultaneously by solving a bilinear program. Equipped with the bilinear program based MAP inference for an unknown graph, we show how to estimate parameters efficiently and effectively with a latent structural SVM. We apply our techniques to predict sport moves (such as serve, volley in tennis) and human activity in TV episodes (such as kiss, hug and Hi-Five). Experimental results show the proposed method outperforms the state-of-the-art.
Game-theoretic wireless CSMA MAC protocols: Measurements from an indoor testbed

Game-theory based carrier sense multiple access (CSMA) protocols for wireless networks have recently emerged as a competitive alternative to classical CSMA based medium access control designs. The advantage of game-theory based approaches lies in the scope of precise mathematical analysis and hence predictable performance compared to approaches based on ad-hoc arguments and heuristics. In this poster, we take up a game-theory based design of wireless contention based medium access control (MAC) and implement it in an indoor IEEE 802.11 wireless testbed with 22 programmable wireless nodes. Our measurements show a remarkably good performance of the design (at the unique Nash equilibrium) in terms of aggregate throughput and short-term fairness vis-a-vis the standard DCF algorithm. To the best of our knowledge, this is the first detailed study of game theory-inspired MAC protocols in a wireless network testbed.
Early prediction of a pedestrian's trajectory at intersections

This paper focuses on the early prediction of a pedestrian's short time trajectory in the course of gait initiation at a crosswalk. We present a comprehensive study on trajectories of adults measured at a public urban intersection using 3D triangulation of stationary video-based marker- and head-detection data. Based on the results of this study we propose two models, a piecewise linear model and a sigmoid model, for predicting the trajectory starting at heel-off. At heel-off, the mean prediction error of the absolute walking distance in real intersection scenarios increases from 12 cm to 26 cm for prediction times of 600 ms to 2.4 s, respectively, for the piecewise linear model. The results provide a basis for vehicle based collision risk estimation resulting in a possible warning of the driver, autonomous emergency braking or evasive steering.
The Option Value of Scientific Uncertainty on Pest - Resistance Development of Transgenic Crops

In this paper the option value of waiting under scientific uncertainty will be derived using the difference between the geometric Brownian motion and the mean reverting process by applying contingent claim analysis. The results will be compared with those generated by either using a geometric Brownian motion or a mean-reverting process only. An example based on the decision problem whether or not to release herbicide tolerant rape seed in the EU will be used to illustrate the differences. The paper contributes to the suggestion made by biologists to further analyze the sensitivity of the results using the real option approach, provides insights about the magnitude of error that can be made by choosing the wrong process, provides a solution to the problem and highlights the implication for the decision of whether or not to release transgenic crops. The results show that scientific uncertainty is less important than one would expect at first hand.
Evaluation of the Effects of Cytochrome P450 Nonsynonymous Single-Nucleotide Polymorphisms on Tanshinol Borneol Ester Metabolism and Inhibition Potential

Nonsynonymous single-nucleotide polymorphisms (nsSNPs) in cytochrome P450 (P450) genes may affect drug metabolism and drug-drug interactions (DDIs), potentially leading to adverse drug reactions. Functional characterization of the nsSNPs in P450 genes is important to help us understand the impact of genetic factors on P450-mediated drug metabolism and DDIs. To evaluate the effects of P450 nsSNPs on the metabolism and inhibition potential of a candidate drug, tanshinol borneol ester (DBZ), we obtained and experimentally validated eight yeast-expressed human P450 isoforms and their nsSNP variants and tested DBZ using these recombinant P450 enzymes. The results suggested that CYP2C8 is the major enzyme responsible for DBZ metabolism. In addition, compared with prototypic CYP2C8, the allelic variant, CYP2C8.3, produced a 54% decrease in the intrinsic clearance of DBZ. The inhibitory potency of DBZ toward CYP3A4 was greater than that toward other P450 isoforms, including CYP1A2, CYP2C8, CYP2C9, CYP2C19, and CYP2D6. Moreover, the inhibitory potency toward three CYP3A4 allelic variants, CYP3A4.2, CYP3A4.12, and CYP3A4.16, was reduced 2- to 10-fold relative to prototype CYP3A4. These results provide useful information for understanding the influence of P450 genetic polymorphisms on DBZ metabolism and may help to design future clinical trials of DBZ. Our results suggest applications for in vitro P450 assays both for basic research in pharmacogenomics and for drug development.
StressDB: A Locally Installable Web-Based Relational Microarray Database Designed for Small User Communities

We have built a microarray database, StressDB, for management of microarray data from our studies on stress-modulated genes in Arabidopsis. StressDB provides small user groups with a locally installable web-based relational microarray database. It has a simple and intuitive architecture and has been designed for cDNA microarray technology users. StressDB uses Windows™ 2000 as the centralized database server with Oracle™ 8i as the relational database management system. It allows users to manage microarray data and data-related biological information over the Internet using a web browser. The source-code is currently available on request from the authors and will soon be made freely available for downloading from our website athttp://arastressdb.cac. psu.edu.
Simulating Quantum Computing: Quantum Express

Quantum Computing (QC) research has gained a lot of momentum recently due to several theoretical analyses that indicate that QC is significantly more efficient at solving certain classes of problems than classical computing. While experimental validation will ultimately be required, the primitive nature of current QC hardware leaves practical testing limited to trivial examples. Thus, a robust simulator is needed to study complex QC issues. Most QC simulators model ideal operations, and thus cannot predict the actual time required to execute an algorithm or quantify the effects of errors in the calculation. We have developed a novel QC simulator that models physical hardware implementations. This simulator not only allows the accurate simulation of quantum algorithms on various hardware implementations, but also takes an important step towards providing a framework to determine their true performance and vulnerability to errors.
Effects of stretching on menopausal and depressive symptoms in middle-aged women: a randomized controlled trial

Objective:Exercise may help alleviate menopausal and depressive symptoms in middle-aged women, but sufficient evidence does not currently exist to fully support this theory. Whereas frequent moderate- to vigorous-intensity exercise may be associated with the risk of menopausal hot flashes, light-intensity exercise, such as stretching, is not likely to increase the occurrence of hot flashes. Little is, however, known about the effects of light-intensity exercise on menopausal and depressive symptoms. We examined the effects of a 3-week stretching program on the menopausal and depressive symptoms in middle-aged, Japanese women. Methods:Forty Japanese women, aged 40 to 61 years, were recruited (mean age, 51.1 ± 7.3 y). The participants were randomly assigned to either a stretching or a control group. The stretching group (n = 20) participated in a 3-week intervention program that involved 10 minutes of daily stretching, just before bedtime. The control group (n = 20) was assigned to a waiting list. Menopausal symptoms were evaluated using the Simplified Menopausal Index, which measures vasomotor, psychological, and somatic symptoms. Depressive symptoms were assessed using the Self-Rating Depression Scale. Results:The compliance rate was 75.8% during the 3-week intervention program. The total Simplified Menopausal Index scores, including the vasomotor, psychological, and somatic symptoms, and the Self-Rating Depression Scale scores significantly decreased in the stretching group compared with that in the control group. No adverse events, including increased hot flashes, were reported by the participants during the study period. Conclusions:These findings suggest that 10 minutes of stretching before bedtime decreases menopausal and depressive symptoms in middle-aged, Japanese women.
Use of Implantable Cardioverter Defibrillators in Heart Failure Patients and Risk of Mortality: A Meta-Analysis

Background The purpose of this study was to evaluate the effect of implantable cardioverter defibrillators (ICD) in heart failure (HF) patients compared to pharmacologic/conventional management. Material/Methods We searched PubMed, Embase, and Springer Link Library databases up to February 10th, 2014. Pooled risk ratio (RR) and 95% confidence interval (CI) for the mortality of the patients with HF were collected and calculated in a fixed-effects model or a random-effects model, as appropriate. Summary effect estimates were also stratified by sex and follow-up time. Egger’s regression asymmetry tests were utilized for publication bias detection. Results A total of 7 separate studies including 15 520 patients (10 801 ICD cases and 4719 controls) with HF were considered in the meta-analysis. The overall estimates showed that ICD could statistically significantly reduce the mortality of male (RR=0.73, 95% CI: 0.66–0.80) and female (RR=0.75, 95% CI: 0.63–0.90) patients. In addition, the further stratification subgroup analysis indicated that ICD presented a significant reduction (male: RR=0.72, 95% CI: 0.64–0.81; female: RR=0.69, 95% CI: 0.56–0.85) of mortality after 2–3 years of ICD therapy. The RR (95% CI) effects of mortality after 4–5 years of ICD therapy for males and females were 0.76 (0.51–1.14) and 0.96 (0.68–1.37), respectively. Conclusions This meta-analysis suggests that ICD could reduce HF patient mortality despite the sex difference.
Phone Recognition for Mixed Speech Signals : Comparison of Human Auditory Cortex and Machine Performance

It is well known that human beings can often attend to a single sound source within a mixed signal from multiple sources, and that unaided automatic speech recognition (without the benefit of effective blind source separation) is quite poor at this task. Here we report on the analysis of human cortical signals to demonstrate the relative robustness of these signals to the mixed signal phenomenon, which is contrasted to a deep neural network-based ASR system. Confirming this difference with a carefully designed experiment is the first step towards ultimately improving blind source separation for the purpose of speech recognition; in particular, the design of features extracted from the neural signals is leading to insights about the corresponding feature extraction on the acoustic side, e.g., for CASA systems of the future.
Neuronal Injury External to the Retina Rapidly Activates Retinal Glia, Followed by Elevation of Markers for Cell Cycle Re-Entry and Death in Retinal Ganglion Cells

Retinal ganglion cells (RGCs) are neurons that relay visual signals from the retina to the brain. The RGC cell bodies reside in the retina and their fibers form the optic nerve. Full transection (axotomy) of the optic nerve is an extra-retinal injury model of RGC degeneration. Optic nerve transection permits time-kinetic studies of neurodegenerative mechanisms in neurons and resident glia of the retina, the early events of which are reported here. One day after injury, and before atrophy of RGC cell bodies was apparent, glia had increased levels of phospho-Akt, phospho-S6, and phospho-ERK1/2; however, these signals were not detected in injured RGCs. Three days after injury there were increased levels of phospho-Rb and cyclin A proteins detected in RGCs, whereas these signals were not detected in glia. DNA hyperploidy was also detected in RGCs, indicative of cell cycle re-entry by these post-mitotic neurons. These events culminated in RGC death, which is delayed by pharmacological inhibition of the MAPK/ERK pathway. Our data show that a remote injury to RGC axons rapidly conveys a signal that activates retinal glia, followed by RGC cell cycle re-entry, DNA hyperploidy, and neuronal death that is delayed by preventing glial MAPK/ERK activation. These results demonstrate that complex and variable neuro-glia interactions regulate healthy and injured states in the adult mammalian retina.
Assessing the Narratives of the Role of Higher Education in Northern Ghana: The Case of University for Development Studies

Purpose: The main purpose of this study was to examine the role of University of Development Studies (UDS) in enhancing socio-economic development in northern Ghana, and secondly, to ascertain whether or not knowledge production and the universities are part of national development strategy.Methodology: In aiming to achieve the descriptive and exploratory objective of the study, the research design adopted for this study was a Case study. The study employed a qualitative approach as its research strategy. A semi-structured interview guide and document analysis was used to answer the research questions. A critical data analysis was done based on open-coding, axial coding, and selective coding.Results: The study revealed that the ‘university as an instrument’ and ‘university as an ancillary’ were the dominant notion emphasized as the key role of UDS, which in essence translate into minimal or somewhat absence of use of Knowledge production and the university in national development strategy.Policy Recommendation: It is recommended that a policy framework should be agreed by key stakeholders that will link the university activities to national development plan which will not only stimulate socio-economic development but to contribute towards the global knowledge economy since global happenings has permeated both national and local levels.
The Effects of the Asian Financial Crisis on Accounting Conservatism in Indonesia

This study examines the extent of conservatism in publicly listed Indonesian companies prior to and following the Asian financial crisis. This study finds that prior to the crisis, share returns did not lead earnings, and accounting practices in Indonesia failed to utilise accruals for reducing cash flow noise as well as to demonstrate conservatism in financial reporting preparation. In the post-crisis period, although there is evidence that stock returns led earnings and that accruals were utilised properly in noise reductions, accounting practices in Indonesia still did not exhibit the accepted level of conservatism.
May We Have Your Attention: Analysis of a Selective Attention Task

In this paper we present a deeper analysis than has previously been carried out of a selective attention problem, and the evolution of continuous-time recurrent neural networks to solve it. We show that the task has a rich structure, and agents must solve a variety of subproblems to perform well. We consider the relationship between the complexity of an agent and the ease with which it can evolve behavior that generalizes well across subproblems, and demonstrate a shaping protocol that improves generalization.
MTG2: an efficient algorithm for multivariate linear mixed model analysis based on genomic information

We have developed an algorithm for genetic analysis of complex traits using genome-wide SNPs in a linear mixed model framework. Compared to current standard REML software based on the mixed model equation, our method could be more than 1000 times faster. The advantage is largest when there is only a single genetic covariance structure. The method is particularly useful for multivariate analysis, including multitrait models and random regression models for studying reaction norms. We applied our proposed method to publicly available mice and human data and discuss advantages and limitations. Availability: MTG2 is available in https://sites.google. com/site/honglee0707/mtg2. Contact: hong.lee@une.edu. au Supplementary information: Supplementary data are available.