Miracle-dz/UniFAR-FTUs huggingface dataset:
Yes-Associated Protein (YAP) Modulates Oncogenic Features and Radiation Sensitivity in Endometrial Cancer

Background Yes-associated protein (YAP) is a transcriptional co-activator and regulates cell proliferation and apoptosis. We investigated the clinical and biological significance of YAP in endometrial cancer (EMCA). Methods YAP expression in 150 primary tumor tissues from patients with EMCA was evaluated by immunohistochemistry and its association with clinicopathological data was assessed. The biological functions of YAP were determined in EMCA cell lines through knockdown/overexpression of YAP. The role of YAP in modulating radiation sensitivity was also investigated in EMCA cells. Results Increased nuclear YAP expression was significantly associated with higher grade, stage, lympho-vascular space invasion, postoperative recurrence/metastasis and overall survival in estrogen mediated EMCA, called type 1 cancer (p = 0.019, = 0.028, = 0.0008, = 0.046 and = 0.015, respectively). In multivariate analysis, nuclear YAP expression was confirmed as an independent prognostic factor for overall survival in type 1 EMCA. YAP knockdown by siRNA resulted in a significant decrease in cell proliferation (p<0.05), anchorage-dependent growth (p = 0.015) and migration/invasion (p<0.05), and a significant increase in the number of cells in G0/G1 phase (p = 0.002). Conversely, YAP overexpression promoted cell proliferation. Clonogenic assay demonstrated enhanced radiosensitivity by approximately 36% in YAP inhibited cells. Conclusions Since YAP functions as a transcriptional co-activator, its differential localization in the nucleus of cancer cells and subsequent impact on cell proliferation could have important consequences with respect to its role as an oncogene in EMCA. Nuclear YAP expression could be useful as a prognostic indicator or therapeutic target and predict radiation sensitivity in patients with EMCA.
COACHES, CLIMATES, “FIELD” GOALS, AND EFFICACY: A “DE-CONSTRUCTION” OF THE MASTERY-APPROACH TO COACHING AND EXAMINATION OF RELATIONSHIPS TO PSYCHOSOCIAL OUTCOMES IN A YOUTH FOOTBALL PLAYER DEVELOPMENT PROGRAM.

Title of dissertation: COACHES, CLIMATES, “FIELD” GOALS, AND EFFICACY: A “DE-CONSTRUCTION” OF THE MASTERY-APPROACH TO COACHING AND EXAMINATION OF RELATIONSHIPS TO PSYCHOSOCIAL OUTCOMES IN A YOUTH FOOTBALL PLAYER DEVELOPMENT PROGRAM. Jay David Goldstein, Doctor of Philosophy, 2016 Dissertation directed by: Professor Seppo E. Iso-Ahola Department of Kinesiology In support of the achievement goal theory (AGT), empirical research has demonstrated psychosocial benefits of the mastery-oriented learning climate. In this study, we examined the effects of perceived coaching behaviors on various indicators of psychosocial well-being (competitive anxiety, self-esteem, perceived competence, enjoyment, and future intentions for participation), as mediated by perceptions of the coach-initiated motivational climate, achievement goal orientations and perceptions of sport-specific skills efficacy. Using a pre-post test design, 1,464 boys, ages 10-15 (M = 12.84 years, SD = 1.44), who participated in a series of 12 football skills clinics were surveyed from various locations across the United States. Using structural equation modeling (SEM) path analysis and hierarchical regression analysis, the cumulative direct and indirect effects of the perceived coaching behaviors on the psychosocial variables at post-test were parsed out to determine what types of coaching behaviors are more conducive to the positive psychosocial development of youth athletes. The study demonstrated that how coaching behaviors are perceived impacts the athletes’ perceptions of the motivational climate and achievement goal orientations, as well as self-efficacy beliefs. These effects in turn affect the athletes’ self-esteem, general competence, sport-specific competence, competitive anxiety, enjoyment, and intentions to remain involved in the sport. The findings also clarify how young boys internalize and interpret coaches’ messages through modification of achievement goal orientations and sport-specific efficacy beliefs. COACHES, CLIMATES, “FIELD” GOALS, AND EFFICACY: A “DE-CONSTRUCTION” OF THE MASTERY-APPROACH TO COACHING AND EXAMINATION OF RELATIONSHIPS TO PSYCHOSOCIAL OUTCOMES IN A YOUTH FOOTBALL PLAYER DEVELOPMENT PROGRAM.
A statistical approach to circle tracking

By applying an edge detection algorithm the silhouettes of objects can be efficiently detected in an image or tracked through multiple frames. Traditional methods of object detection ignore information about an object being tracked. This information can be used to reduce processing time and increase accuracy of object detection. This paper proposes a method that uses this information to provide a tracking algorithms for circles in images with low processing time. It does this by creating a probability distribution function which it integrates to calculate an estimated object position. The processing time and accuracy of the algorithm is then tested against comparable methods, such as the Randomised Hough Transform. For the parameters given it is more accurate than the Randomised Hough Transform at about a quarter the processing time.
An Interpretation Construction Approach to Constructivist Design

Study is a key concept in making design more fruitful in education. We propose that what students are doing when they construct knowledge is studying. Specifically, we think that the term study captures better what should be going on during knowledge construction then does the term learn. Thus, in designing for knowledge construction we see ourselves as designing Study Support Environments (SSEs) instead of "instructional systems" or "learning environments. " Creating SSEs allows us to create "a place for study in a world of instruction" (McClintock, 1971, " Toward a Place for Study in a World of Instruction"). The core of study is the hermeneutic activity of constructing interpretations. Hermeneutics as a field focused initially on interpretation of texts, but has broadened to interpretation in general (Palmer, 1969; Gadamer, 1976). From this perspective, the basis for cognition (and being in general) is interpretation based on background knowledge and beliefs (Heidegger, 1962; Winograd and Flores, 1986). Consistent with these philosophical arguments for the centrality of interpretation in cognition are the many research results from cognitive psychology showing that understanding involves making a large number of inferences (Black, 1984; Black, 1985). Thus, the key consideration in designing a SSE is fostering the construction of interpretations based on observations and background contextual information. Teachers College, Columbia University has been collaborating with the Dalton School (a K-12 independent school in New York City) on the Dalton Technology Plan. The general aim of this plan is to develop a digital knowledge-base and information infrastructure for all aspects of the K-12 educational experience, and to implement educational strategies designed to make use of this infrastructure, enhancing significantly an already excellent educational experience. In this paper, we describe a framework for SSE design and describe its application to three specific SSEs created as part of the Dalton Technology Plan. After describing the SSEs we report evaluations that demonstrate their effectiveness.
Spatio-Temporal Motion Pattern Modeling of Extremely Crowded Scenes

The abundance of video surveillance systems has created a dire need for computational methods that can assist or even replace human operators. Research in this field, however, has yet to tackle an important real-world scenario: extremely crowded scenes. The excessive amount of people and their activities in extremely crowded scenes present unique challenges to motion-based video analysis. In this paper, we present a novel statistical framework for modeling the motion pattern behavior of extremely crowded scenes. We construct a rich yet compact representation of the local spatio-temporal motion patterns and model their temporal behaviors with a novel, distribution-based Hidden Markov Model (HMM), exploiting the underlying statistical characteristics of the scene. We demonstrate that, by capturing the steady-state behavior of a scene, we can naturally detect unusual events as unlikely motion pattern variations. The experiments show promising results in extremely crowded real-world scenes with complex activities that are hard for even human observers to analyze.
Mixture decompositions of exponential families - using a decomposition of their sample spaces

We study the problem of finding the smallest $m$ such that every element of an exponential family can be written as a mixture of $m$ elements of another exponential family. We propose an approach based on coverings and packings of the face lattice of the corresponding convex support polytopes and results from coding theory. We show that $m=q^{N-1}$ is the smallest number for which any distribution of $N$ $q$-ary variables can be written as mixture of $m$ independent $q$-ary variables. Furthermore, we show that any distribution of $N$ binary variables is a mixture of $m = 2^{N-(k+1)}(1+ 1/(2^k-1))$ elements of the $k$-interaction exponential family.
Effects of amitriptyline and fluoxetine on synaptic plasticity and TNF-α level at hippocampus of streptozotocin-induced diabetic rats

Introduction: Studies have indicated that diabetes mellitus impairs hippocampus. Diabetes increases the risk of depression and treatment with antidepressants may affect learning and memory. The aim of this study was to evaluate the effects of amitriptyline and fluoxetine on synaptic plasticity and TNF-α level in the hippocampus of streptozotocin-induced diabetic rats. Methods: Experimental groups were control, diabetes, diabetes-amitriptyline and diabetes-fluoxetine (n=8 for each experimental group). Three weeks after the induction of diabetes, the rats received treatment with amitriptyline (5 mg/kg) or fluoxetine (5 mg/kg) for 21 days. Long-term potentiation (LTP) in perforant pathdentate gyrus synapses was assessed (by 400 Hz tetanization) for investigating the effect of treatments on synaptic plasticity. Field excitatory post-synaptic potential indices were measured. Finally, TNF-α levels were measured in hippocampus by enzyme-linked immunosorbant assay. Results: Six weeks after the diabetes induction, LTP wasn’t different between the control and the diabetes groups and also no significant differences were observed between the diabetes and the diabetes-treated groups; however, amitriptyline and fluoxetine impaired LTP in diabetic rats and there was a significant difference between the control and the diabetes-treated groups. Comparing to the controls, TNF-α level was increased significantly (P<0.05) only in the diabetes-amitriptyline
A novel model for query over encrypted XML databases

In recent years, there has been increasing concern about “Database as a Service”(DAS) architectures. Data security is the overriding concern in DAS, and encryption is a natural solution. However, queries over encrypted databases are usually inefficient due to a heap of time on the encryption and decryption. In this paper, we present an encryption scheme and XQuery translation model of XML database. The major work and contribution of this paper are as below: 1) Splitting method is proposed in the encryption scheme, in which more flexible encryption granularity is obtained. 2) We put forward the encryption strategy that, by encrypting two or more fragments together, is efficient to resist various kinds of database attack owing to the changed ciphertext distribution and data size by splitting. 3) An XQuery translation model is introduced, by converting the query of XML data into that of relational data, combined with XML Schemas Compression and hash technology, which perform the XQuery language efficiently. Our experimental evaluation shows that our XML database encryption and query model achieves both excellent query efficiency and robust security.
Land Use and Travel Behaviour: Expected Effects from the Perspective of Utility Theory and Activity-Based Theories

Assumptions about the effects of various land-use characteristics on travel patterns have found their way into diverse concepts of planning and design, such as the compact city and neighbourhood-design principles. In general, these concepts aim at reducing travel distances and reducing car-travel speed, as it is assumed that as travel distances are shorter, individuals will travel less, and the relative competitive position of slower modes is increased. Although some literature supports the link between land use and travel behaviour, for the greater part limited effects have been concluded, whereas in others it has been concluded that there is virtually no effect. We argue that the effects fall short of the expectations advocated by the land-use concepts, because of shortcomings behind assumptions concerning the relationships between land use and travel behaviour. We argue that utility-based and activity-based theories add some extra insights. Various behavioural responses in terms of travel-time changes are possible, depending on whether travel time is minimised, benefits maximised, or activity patterns optimised. It is concluded that the contribution of compact urban designs to reduction on travel may not be as straightforward as is suggested by their advocates. In any case, a simplified distance-oriented and trip-oriented approach is unable to examine complex behaviour, and a broader framework of space and time is needed.
The Voltage Dependence of a Cloned Mammalian Renal Type II Na+/Pi Cotransporter (NaPi-2)

The voltage dependence of the rat renal type II Na+/Pi cotransporter (NaPi-2) was investigated by expressing NaPi-2 in Xenopus laevis oocytes and applying the two-electrode voltage clamp. In the steady state, superfusion with inorganic phosphate (Pi) induced inward currents (Ip) in the presence of 96 mM Na+ over the potential range −140 ≤ V ≤ +40 mV. With Pi as the variable substrate, the apparent affinity constant (K m Pi) was strongly dependent on Na+, increasing sixfold for a twofold reduction in external Na+. K m Pi increased with depolarizing voltage and was more sensitive to voltage at reduced Na+. The Hill coefficient was close to unity and the predicted maximum Ip (Ipmax) was 40% smaller at 50 mM Na+. With Na+ as the variable substrate, K m Na was weakly dependent on both Pi and voltage, the Hill coefficient was close to 3 and Ipmax was independent of Pi at −50 mV. The competitive inhibitor phosphonoformic acid suppressed the steady state holding current in a Na+-dependent manner, indicating the existence of uncoupled Na+ slippage. Voltage steps induced pre–steady state relaxations typical for Na+-coupled cotransporters. NaPi-2-dependent relaxations were quantitated by a single, voltage-dependent exponential. At 96 mM Na+, a Boltzmann function was fit to the steady state charge distribution (Q-V) to give a midpoint voltage (V0.5) in the range −20 to −50 mV and an apparent valency of ∼0.5 e−. V0.5 became more negative as Na+ was reduced. Pi suppressed relaxations in a dose-dependent manner, but had little effect on their voltage dependence. Reducing external pH shifted V0.5 to depolarizing potentials and suppressed relaxations in the absence of Na+, suggesting that protons interact with the unloaded carrier. These findings were incorporated into an ordered kinetic model whereby Na+ is the first and last substrate to bind, and the observed voltage dependence arises from the unloaded carrier and first Na+ binding step.
Image analysis for denoising full‐field frequency‐domain fluorescence lifetime images

Video‐rate fluorescence lifetime‐resolved imaging microscopy (FLIM) is a quantitative imaging technique for measuring dynamic processes in biological specimens. FLIM offers valuable information in addition to simple fluorescence intensity imaging; for instance, the fluorescence lifetime is sensitive to the microenvironment of the fluorophore allowing reliable differentiation between concentration differences and dynamic quenching. Homodyne FLIM is a full‐field frequency‐domain technique for imaging fluorescence lifetimes at every pixel of a fluorescence image simultaneously. If a single modulation frequency is used, video‐rate image acquisition is possible. Homodyne FLIM uses a gain‐modulated image intensified charge‐coupled device (ICCD) detector, which unfortunately is a major contribution to the noise of the measurement. Here we introduce image analysis for denoising homodyne FLIM data. The denoising routine is fast, improves the extraction of the fluorescence lifetime value(s) and increases the sensitivity and fluorescence lifetime resolving power of the FLIM instrument. The spatial resolution (especially the high spatial frequencies not related to noise) of the FLIM image is preserved, because the denoising routine does not blur or smooth the image. By eliminating the random noise known to be specific to photon noise and from the intensifier amplification, the fidelity of the spatial resolution is improved. The polar plot projection, a rapid FLIM analysis method, is used to demonstrate the effectiveness of the denoising routine with exemplary data from both physical and complex biological samples. We also suggest broader impacts of the image analysis for other fluorescence microscopy techniques (e.g. super‐resolution imaging).
Requirements engineering for a pervasive health care system

We describe requirements engineering for a new pervasive health care system for hospitals in Denmark. The chosen requirements engineering approach composes iterative prototyping and explicit environment description in terms of workflow modelling. New work processes and their proposed computer support are represented via a combination of prose, formal models, and animation. The representation enables various stakeholders to make interactive investigations of requirements for the system in the context of the envisioned work processes. We describe lessons learned from collaboration between users and system developers in engineering the requirements for the new system.
Public discourse and news consumption on online social media: A quantitative, cross-platform analysis of the Italian Referendum

The rising attention to the spreading of fake news and unsubstantiated rumors on online social media and the pivotal role played by confirmation bias led researchers to investigate different aspects of the phenomenon. Experimental evidence showed that confirmatory information gets accepted even if containing deliberately false claims while dissenting information is mainly ignored or might even increase group polarization. It seems reasonable that, to address misinformation problem properly, we have to understand the main determinants behind content consumption and the emergence of narratives on online social media. In this paper we address such a challenge by focusing on the discussion around the Italian Constitutional Referendum by conducting a quantitative, cross-platform analysis on both Facebook public pages and Twitter accounts. We observe the spontaneous emergence of well-separated communities on both platforms. Such a segregation is completely spontaneous, since no categorization of contents was performed a priori. By exploring the dynamics behind the discussion, we find that users tend to restrict their attention to a specific set of Facebook pages/Twitter accounts. Finally, taking advantage of automatic topic extraction and sentiment analysis techniques, we are able to identify the most controversial topics inside and across both platforms. We measure the distance between how a certain topic is presented in the posts/tweets and the related emotional response of users. Our results provide interesting insights for the understanding of the evolution of the core narratives behind different echo chambers and for the early detection of massive viral phenomena around false claims.
Code Dissemination in Sensor Networks with MDeluge

In today's wireless sensor networks there is a need to improve macro programming of the sensor nodes so that sensor nodes can execute various applications in a flexible manner. There is a need to contribute to macro programming of wireless sensor networks by developing new code dissemination techniques which can disseminate the code into designated sensor nodes. We present a new algorithm called multicast deluge (MDeluge) which can be used to disseminate the code image into a designated subnet of a wireless sensor network. MDeluge disseminates code in the sensor network using a tree which is formed when the sensor nodes send code request messages. Micro server keeps the code and sends it based on the requests. MDeluge disseminates binary code as well as capsules of Mate. We extend MDeluge for the sensor networks that are geographically distributed and that have moving nodes. Assuming a grid structured wireless sensor network we present an analysis of various message costs as well as the overall cost of data messages of MDeluge. Simulation of MDeluge shows that MDeluge performs better than Deluge to disseminate the code into designated sensor nodes
Text compression using lexicographic permutation of binary strings

Text messages are generally encoded by performing table look-up on fixed length code tables. In this paper, a lossless text compression algorithm which works on the principle of entropy reduction is proposed. Characters in a text message in any language are generally encoded using a binary string with a Unique Lexicographical Rank (ULR). A corresponding Maximum Rank(MR) for any binary string can be computed using lexicographical permutation. Reducing the MR of the binary string results in considerable reduction in the number of bits to be transmitted. MR reduction is achieved in this work by using character frequency based encoding models. Uni-gram, bi-gram and tri-gram models are used herein. Experiments on text compression are conducted on the Calgary Corpus and Project Gutenberg databases. Experiments on text compression are conducted on the Calgary and The Project Gutenberg corpus. Results indicate a significant increase in compression ratio.
Programming voltage reduction in phase change cells with conventional structure

A new operation strategy has been proposed to reduce the programming voltage in RESET operation of phase change memory (PCM). The amorphous state generated after first pulse would restrict the current flowing through the phase change materials, increasing the heat efficiency. Thus, the amorphous state in the second pulse would increase. The accumulative amorphous state would cover the bottom electrode finally. Thus, RESET operation commences successfully. In new RESET operation strategy, the voltage pulse could consist of small amplitude and width voltage pulses (1V/35ns). The programming voltage is reduced with conventional structure, reducing costing on refining cell structure and power consumption.
Segmentation of brain MR image using fuzzy local Gaussian mixture model with bias field correction

Accurate brain tissue segmentation from magnetic resonance (MR) images is an essential step in quantitative brain image analysis. However, due to the existence of noise and intensity in-homogeneity in brain MR images, many segmentation algorithms suffer from limited accuracy. Here, we assume that the local image data within each voxel’s neighborhood satisfy the Gaussian mixture model (GMM), and thus propose the fuzzy local GMM (FLGMM) algorithm for automated brain MR image segmentation with bias field correction. This algorithm estimates the segmentation result that maximizes the posterior probability by minimizing an objective energy function, in which a truncated Gaussian kernel function is used to impose the spatial constraint and fuzzy memberships are employed to balance the contribution of each GMM. Our results show that the proposed algorithm can largely overcome the difficulties raised by noise, low contrast, and bias field, and substantially improve the accuracy of brain MR image segmentation.