Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating articulatory setting - pauses, ready position, and rest - using real-time MRI

We present a novel automatic procedure to analyze ―articulatory setting (AS)‖ or ―basis of articulation‖ using realtime magnetic resonance images (rt-MRI) of the human vocal tract recorded for read and spontaneously spoken speech. We extract relevant frames of inter-speech pauses (ISPs) and rest positions from MRI sequences of read and spontaneous speech and use automatically-extracted features to quantify areas of different regions of the vocal tract as well as the angle of the jaw. Significant differences were found between the ASs adopted for ISPs in read and spontaneous speech, as well as those between ISPs and absolute rest positions. We further contrast differences between ASs adopted when the person is ready to speak as opposed to an absolute rest position.
The impact of lesson study professional development on teacher self-efficacy and outcome expectancy

The purpose of this mixed methods case study was to examine the impact of lesson study professional development on teacher self-efficacy and outcome expectancy using Bandura’s Social Cognitive Theory as a framework (1977). The focus of this lesson study was implementing Common Core State Standards for mathematics. Thirteen K-6 teachers participated in the lesson study professional development, completed a pre/post Mathematics Teaching Efficacy and Expectancy Beliefs Inventory (MTEEBI) and completed ongoing journaling prompts while the researcher conducted observations throughout the process. Qualitative and quantitative data gathered in this research indicated the lesson study professional development had a positive impact on both self-efficacy and outcome expectancy of the teacher participants. Though the teachers possessed a satisfactory level of self-efficacy and outcome expectancy at the onset of the study, a measurable gain was evident. Comparison of the pre and post MTEEBI surveys, through statistical analysis using a Paired-Samples t-test, indicated a significant positive change in both self-efficacy and outcome expectancy scores. Though growth for both constructs was significant at the . 05 level of probability, self-efficacy growth was greater than outcome expectancy. This finding is supported in historical research of the challenge of yielding outcome expectancy growth. The qualitative analysis of observations and journal prompts corroborated the MTEEBI results, indicating a majority of the teachers’ selfefficacy and outcome expectancy beliefs were positively impacted by the lesson study professional development. Bandura’s four sources of efficacy (mastery experiences, modeling, verbal/social persuasion, physiological responses) positively impacted personal self-efficacy, while three of the four sources (mastery experiences, modeling, physiological responses) impacted outcome expectancy. Qualitative data indicated mastery experiences were most critical for both constructs. Lesson study professional development is a natural catalyst for addressing Bandura’s four sources of efficacy and thus building self-efficacy and outcome expectancy. Given the demands of rigorous educational reform, lesson study professional development is a promising approach to positively impact teacher self-efficacy and outcome expectancy, through engaging Bandura’s four sources of efficacy to develop and strengthen these beliefs. Therefore lesson study ought to be a more frequent component of teacher professional development and teacher preparation. THE IMPACT OF LESSON STUDY PROFESSIONAL DEVELOPMENT ON TEACHER SELF-EFFICACY AND OUTCOME EXPECTANCY
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This perspective paper explores principles of unsupervised learning and how they relate to face recognition. Dependency coding and information maximization appear to be central principles in neural coding early in the visual system. These principles may be relevant to how we think about higher visual processes such as face recognition as well. The paper first reviews examples of dependency learning in biological vision, along with principles of optimal information transfer and information maximization. Next, we examine algorithms for face recognition by computer from a perspective of information maximization. The eigenface approach can be considered as an unsupervised system that learns the first-and second-order dependencies among face image pixels. Eigenfaces maximize information transfer only in the case where the input distributions are Gaussian. Independent component analysis (ICA) learns high-order dependencies in addition to first-and second-order relations, and maximizes information transfer for a more general set of input distributions. Face representations based on ICA gave better recognition performance than eigenfaces, supporting the theory that information maximization is a good strategy for high level visual functions such as face recognition. Finally, we review perceptual studies suggesting that dependency learning is relevant to human face perception as well, and present an information maximization account of perceptual effects such as the atypicality bias, and face adaptation aftereffects.
Investigating the effect of virtual reality application on teaching assistance for machine tools operation education

With the assistance of developed virtual CNC machine tools, industry and school can alleviate the educating and training constraints on CNC practice courses. However, whether the design product (virtual machine tool) is consistent with student's expectation is also worthwhile to study. Therefore, in this paper, we investigated the effect of VR on the student's intention to learn the designed VR machine tool in CNC practice course based on affordance theory. The proposed theoretical model was empirically evaluated by using survey data collected from 170 students concerning their perceptions of affordance for a designed VR machine tool. The research result might provide a reference for academy and industry to design an improved VR system to satisfy student's expectation.
On calibrating a camera network using parabolic trajectories of a bouncing ball

Camera networks are often used in visual surveillance systems for wide-range monitoring. In this paper, we present a novel method for calibrating a camera network, which uses the trajectory of a bouncing ball as the calibration data. An important feature of our method is the use of the parabolic property of a ball's bouncing trajectory. This parabolic trajectory lies on a plane, called the parabolic trajectory plane (PT-plane), so that the relationship between the trajectory's points and their corresponding image points is a homography. Combining the vertical velocity determined by the earth's gravity and the horizontal velocity calculated from the homography, we can compute the 2D coordinates of the trajectory points on the PT-plane. By throwing the ball multiple times, we obtain calibration points on multiple planes for calibrating both intrinsic and extrinsic parameters of the networked cameras. Experimental results have demonstrated the feasibility and accuracy of the proposed method.
Consensus-based Fuzzy TOPSIS Approach for Supply Chain Coordination: Application to Robot Selection Problem

Abstract In hotly competitive international industrial and economic environments, supply chain coordination (SCC) is one of active research topics in production and operation management. In this research work, we present a new consensus-based fuzzy TOPSIS approach for supply chain coordination problem. It is formulated as a multi-criteria group decision making (MCGDM) problem and solved by combining consensus-based possibility measure with TOPSIS method in a fuzzy environment. To demonstrate the applicability of the proposed approach, a simple example of robot selection problem is presented and the numerical results analyzed. Moreover, using the Levenshtein distance, the deviation between individual solutions and group solution is analyzed.
Unternehmensnetzwerke : architekturen, strukturen und strategien

Anstatt Netzwerke nur aus der Sicht einzelner Akteure zu betrachten, richten die Autoren ihren Blick auf die multilaterale Zusammenarbeit. Wissenschaftler, Unternehmens- und Rechtsberater diskutieren Konzepte wie Netzwerkgut oder laterale Governance, auf deren Grundlage Netzwerke ausgestaltet und ihre Innovationskraft gefordert werden kann. Auch die Wahl der Rechtsform, der Controllinginstrumente sowie der Einsatz von Kommunikationstechnologien werden thematisiert. Erfolgsfaktoren arbeiten die Autoren anhand detaillierter Fallstudien heraus. "
Understanding tire/road stick-slip interactions with embedded rubber force sensors

Pneumatic tires are widely used for mobile robots and vehicles. Tire/road interactions play an important role in the safe operation and design of these systems. In this paper, we focus on the tire/road contact problem and study the stick-slip interactions between the stationary tire and the firm road. A pressure-sensitive, electric conductive rubber sensor is embedded inside the tire rubber layer to measure the force distributions. We analyze the frictional forces and deformation distributions using a cantilever beam-based modeling approach. The analytical results explain the stick-slip evolution between the tire and the road. The analyses and models are also validated by experiments.
Nanoindentation of 35 Virus Capsids in a Molecular Model: Relating Mechanical Properties to Structure

A coarse-grained model is used to study the mechanical response of 35 virus capsids of symmetries T = 1, T = 2, T = 3, pseudo T = 3, T = 4, and T = 7. The model is based on the native structure of the proteins that constitute the capsids and is described in terms of the C atoms associated with each amino acid. The number of these atoms ranges between 8 460 (for SPMV – satellite panicum mosaic virus) and 135 780 (for NBV – nudaureli virus). Nanoindentation by a broad AFM tip is modeled as compression between two planes: either both flat or one flat and one curved. Plots of the compressive force versus plate separation show a variety of behaviors, but in each case there is an elastic region which extends to a characteristic force . Crossing results in a drop in the force and irreversible damage. Across the 35 capsids studied, both and the elastic stiffness are observed to vary by a factor of 20. The changes in mechanical properties do not correlate simply with virus size or symmetry. There is a strong connection to the mean coordination number , defined as the mean number of interactions to neighboring amino acids. The Young's modulus for thin shell capsids rises roughly quadratically with , where 6 is the minimum coordination for elastic stability in three dimensions.
Code Compression to Reduce Cache Accesses

Code compression has been shown to be an effective technique to reduce code size in memory constrained embedded systems. It has also been used as a way to increase cache hits, thus reducing power consumption and improving performance. This report proposes a simple dictionary-based technique for code compression. It describes an approach to mix static/dynamic instruction profiling so as to trade-off compression ratio for performance. Compressed instructions are stored as variable-size indices into fixed-size codewords, thus reducing dictionary entry superpositions and compressed code misalignments simultaneously. Moreover, a decompressor buffering scheme is proposed that considerably decreases cache lookups. Experimental results, using the LEON SparcV8 processor and a program mix from MiBench and Mediabench, show that our approach halves the number of cache accesses while produce compression ratios as low as 56%.
A distributed shared key generation procedure using fractional keys

We present a new class of distributed key generation and recovery algorithms suitable for group communication systems where the group membership is either static or slowly time-varying, and must be tightly controlled. The proposed key generation approach allows entities which may have only partial trust in each other to jointly generate a shared key without the aid of an external third party. The shared key is generated using a strong one-way function of the group parameter. This scheme also has perfect forward secrecy. The validity of key generation can be checked using verifiable secret sharing techniques. The key retrieval method does not require the keys to be stored in an external retrieval center. We note that many internet-based applications may have these requirements. Fulfillment of these requirements is realized through the use of fractional keys-a distributed technique developed to enhance the security of distributed systems in a non-cryptographic manner.
Developing empathic leadership through self-transformation

This thesis works to deepen my understandings of empathic intelligence in relation to leadership. It builds upon experiences I have had as an education leader and as a fellowship holder in the United States where I discussed strategy and practice with key theorists, visited and observed at selected schools, and interviewed students and teachers, as well as principals who uniquely led their educational communities. The professional relationships formed during this experience provoked questions about my own leadership style and practice as principal of a rural Tasmanian High School. From these experiences I have developed a thesis that excellent school leaders demonstrate high degrees of empathic intelligence. This work explores the theory of empathic intelligence and how it can elucidate understanding of teaching and leadership. This thesis is structured by five key intentions, which are to: •unfold an understanding of empathic intelligence informed by Arnold (2005); •explore how empathic intelligence might be understood and enacted in a Tasmanian high school; •use these understandings to unfold a concept of effective leadership at a range of levels in the Tasmanian system; •reflect upon how I might extend my ability as an empathic leader; and •critique and deepen the theory of empathic intelligence (Arnold 2005). To inform this study and support my personal theorising of highly effective empathic leadership, I critique theories of intelligence and leadership developed by Duignan (2004, 2003, 2002), Arnold (2005), Gardner (2000, 1993, 1991), Blythe et al. (1998) and Perkins (1992). I respond to my thesis intentions through processes of interpreting conversations (Davis et al. 2000; Van Manen 1990), narratives (Eakin 1999; Richardson 2000) and fictionalised letters (Ospina & Dodge 2005; Ellis & Bochner 2000). The processes of inquiry support me to: uncover four key elements of powerful empathic leadership (enthusiasm, engagement, expertise and, of course, empathy); deepen this theory by including the additional elements of trust and honesty; and suggest that links need to be developed through professional relationships. The inquiry then uncovers new questions about how empathic leadership is enacted in a Tasmanian High School. This inquiry suggests how powerful empathic leadership might work at personal, school and systemic levels. The inquiry is drawn to a close as I unfold a set of new questions that reflect my deepened understanding of empathic leadership.
View sharing system for motion transmission

We are developing 'view sharing' system for supporting a remote corporative work. The view sharing is constructed from the video-see-through head mounted displays (VST-HMD) and motion trackers. This system allows two users in remote places to share their first-person views each other. The users can share what the other user is seeing, and furthermore the users can correspond their spatial perception, motion and head movement. By sharing those sensations, the non-verbal skills can be transmitted from skilled person to the non-skilled person. Using this system expert in remote place can instruct the non-skilled person to improve task performance.
Bivariate Estimator for cDNA Microarray Images Using Complex Wavelets

Removal of noise is an essential step in the preprocessing of microarray images for obtaining betterquality gene expression measurements. Wavelet-based methods for denoising of images are very successful. However, for cDNA microarray images, existing methods are not as efficient because they fail to take into account linear dependencies that exist between wavelet coefficients of the red and green channel images. To address this issue, a bivariate MAP estimator is proposed in the complex wavelet transform (CWT) domain that jointly estimates wavelet coefficients in the two channels. The CWT is preferable to the traditional discrete wavelet transform for denoising of microarray images owing to its good directional selectivity and shift-invariance properties. Both properties ensure better detection of edges in the spots. The proposed method is compared with other locallyadaptive CWT-based denoising techniques using simulation experiments. Results show that our method achieves improved noise reduction performance as compared to others in terms of the mean squared error.
17β-estradiol upregulates GREB1 and accelerates ovarian tumor progression in vivo

Exogenous 17β‐estradiol (E2) accelerates the progression of ovarian cancer in the transgenic tgCAG‐LS‐TAg mouse model of the disease. We hypothesized that E2 has direct effects on ovarian cancer cells and this study was designed to determine the molecular mechanisms by which E2 accelerates ovarian tumor progression. Mouse ovarian cancer ascites (MAS) cell lines were derived from tgCAG‐LS‐TAg mice. Following intraperitoneal engraftment of two MAS cell lines, MASC1 and MASE2, into SCID mice, exogenous E2 significantly decreased the survival time and increased the tumor burden. Microarray analysis performed on MASE2‐derived tumors treated with E2 or placebo showed that E2 treatment caused the upregulation of 197 genes and the downregulation of 55 genes. The expression of gene regulated by estrogen in breast cancer 1 (Greb1) was upregulated in mouse tumors treated with E2 and was overexpressed in human ovarian cancers relative to human ovarian surface epithelium, suggesting a role for GREB1 in human ovarian tumor progression. RNA interference‐mediated knockdown of GREB1 in MASE2 cells decreased their proliferation rate in vitro and increased survival time in mice engrafted with the cells. These results emphasize the importance of E2 in ovarian tumor progression and identify Greb1 as a novel gene target for therapeutic intervention.
Verteilungsbasierte kausale Inferenzmodelle zur Schätzung von Therapieffekten in randomisierten kontrollierten klinischen Studien

In prospective randomized trials differences in population based means can be considered as estimates of mean causal exposure or treatment effects. Nevertheless, occurence of intermediate events in the course of a trial may lead to biased estimates of treatment effects. Particularly this will be the case, if the probability of such an event is not independent of initial treatment allocation and the intermediate event is both a risk factor for the main outcome parameter (e.g. survival) and a predictor of subsequent treatment. This situation was referred as 'treatment by indication problem' by Robins (1992) and is common in epidemiological trials. Robins demonstrated that the usual approach of an adjusted estimation of treatment effect using a time-dependent proportional hazards model may be biased in this situation, whether or not one further adjusts for past confounder history in the analysis. In this thesis a novel inference procedure for randomized trials is introduced which is based on the idea of Robin's G-Estimation principle but particularly consideres specifics of randomized trials. The suggested procedure allows for an unbiased and consistent estimation of a treatment effect parameter (or paremeter vector) which is connected by a real-valued function to the parameters of an underlying distribution of survival times. In fulfilment of the requirements of a causal individual-level based model, a link of a subject's observed and counterfactual survival time is directly achieved by the inverse distribution function of survival times in a reference treatment arm. In this term, causal inference is feasible based on the likelihood function and its corresponding test statistics, even under appropriate consideration of time-dependent confounders.
Depth map reconstruction using color-based region merging

This paper presents a novel depth map enhancement method which takes as inputs a single view and an initial depth estimate. A region-based framework is introduced wherein a color-based partition of the image is created and depth uncertainty areas are identified according to the alignment of detected depth discontinuities and region borders. A color-based homogeneity criterion is used to guide a constrained region merging process and reconstruct depth estimates within the uncertainty areas. Experimental results on publicly available test sequences illustrate the potential of the algorithm in significantly improving low quality depth estimates.
Corticotropin-Releasing Factor Receptor 1 and Central Heart Rate Regulation in Mice during Expression of Conditioned Fear

The present study was performed to 1) determine heart rate (HR) effects mediated through central corticotropin-releasing factor receptor subtypes 1 (CRF1) investigate and 2 (CRF2) and 2) to the contribution of endogenous CRF to baseline HR and its fear-induced adjustment in freely moving mice. CRF ligands were injected into both lateral ventricles (i.c.v.) 15 min before the presentation of a conditioned auditory fear stimulus (CS). Initial behavioral results suggest an ovine CRF (oCRF)-mediated enhanced baseline fear and mildly enhanced conditioned auditory fear. In contrast, i.c. v. injection of oCRF (35–210 ng/mouse) dose-dependently decreased baseline HR, increased HR variability, and attenuated the CS-induced tachycardia. This effect is suggested to depend on a combined activation of sympathetic and parasympathetic activity referred to as enhanced sympathovagal antagonism. An extreme bradycardia was elicited by oCRF injection into the lower brainstem. All HR effects were probably mediated by CRF1 because injection of the CRF2-selective agonist mouse urocortin II was ineffective, and the baseline bradycardia by i.c. v. CRF was preserved in CRF2-deficient mice. Injection of various CRF receptor antagonists including the CRF2-selective antisauvagine-30 did not affect the conditioned HR response. This finding suggests that endogenous CRF does not contribute to the fear-mediated tachycardia. Thus, the hypothesis of an involvement of CRF in HR responses of mice to acute aversive stimulation is rejected. Pharmacological evidence points at the involvement of CRF1 in enhanced sympathovagal antagonism, a pathological state contributing to elevated cardiac risk, whereas the physiological role of the brain CRF system in cardiovascular regulation remains to be determined.
Mapping template semantics to SMV

We show how to create a semantics-based, parameterized translator from model-based notations to SMV, using template semantics. Our translator takes as input a specification and a set of user-provided parameters that encode the specification's semantics; it produces an SMV model suitable for model checking. Using such a translator, we can model check a specification that has customized semantics. Our work also shows how to represent complex composition operators, such as rendezvous, in the SMV language, in which there is no matching language construct.