Miracle-dz/UniFAR-FTUs huggingface dataset:
Inhibition of angiogenesis by the antiepidermal growth factor receptor antibody ImClone C225 in androgen-independent prostate cancer growing orthotopically in nude mice.

In human androgen-independent prostate cancer (PCa), epidermal growth factor receptor (EGFR) regulates angiogenesis, tumor growth, and progression. In this study, we evaluated whether the blockade of EGFR by the anti-EGFR antibody ImClone C225 (IMC-C225) inhibited tumor growth and metastasis by inhibiting angiogenesis, and whether paclitaxel enhanced the results of therapy in androgen-independent PCa. PC-3M-LN4 PCa cells were implanted orthotopically in athymic nude mice and treated with i.p. IMC-C225 (1 mg twice a week) and/or paclitaxel (200 microg once a week). In vitro treatment of PC-3M-LN4 with IMC-C225 inhibited EGFR autophosphorylation without any significant antiproliferative effect. In contrast, in vivo therapy with IMC-C225 alone (P < 0.05) or in combination with paclitaxel (P < 0.005) significantly inhibited PCa growth and metastasis. Serum levels of interleukin (IL) 8 were lower after therapy, and IL-8 mRNA expression was down-regulated within the tumors after therapy. The down-regulation of IL-8 correlated with reduced microvessel density. IMC-C225 reduced tumor cell proliferation, enhanced p27(kip1) expression, and induced tumor and endothelial cell apoptosis. These studies indicate that IMC-C225 has significant antitumor effect in this murine model, mediated in part by inhibition of cellular proliferation and angiogenesis, and by enhancement of apoptosis. The simultaneous administration of paclitaxel enhanced this effect.
Institutional Collaboration, Learning and Context: A Case Study of Tasmanian Information Technology Institutions

With increasing devolution of governance, collaboration has become ever more important as a means for community groups, regions and institutions to meet their needs. Firms also use a variety of collaborative arrangements to meet their need to compete effectively in local and global markets. However, for all the growth in collaborative activity, there are many fraught or failed attempts suggesting a need to better understand the processes of collaboration. This thesis contributes to our understanding of institutional collaboration, focusing on institutional collaborative activity, learning and context. Collaboration is not considered as a stand-alone activity, but as an activity that is a learning process influenced by context.
A Review of Inclusive Education in New Zealand

Inclusive education is a worldwide response to the belief that all children have the right to be educated at their local early childhood centre or school. New Zealand’s education system has undergone a series of transformations over the past 20 years, which has included modifications to how schools and their students are funded and managed, and the responsibilities various government departments have for ensuring all children receive the best possible education in a variety of environments. This article outlines those changes, suggests a way forward that will help ensure inclusive education practices in New Zealand match the current policies and rhetoric, and further reinforces the uniqueness that all children bring to their ‘sense’ of inclusion. 2 Electronic Journal for Inclusive Education, Vol. 2, No. 10 [2012], Art. 4 http://corescholar.libraries. wright.edu/ejie/vol2/iss10/4 REVIEW OF INCLUSIVE EDUCATION IN NEW ZEALAND 2
Molecular Characterization of Canine Rabies Virus, Mali, 2006–2013

We genetically characterized 32 canine rabies viruses isolated in Mali during 2006–2013 and identified 3 subgroups that belonged to the Africa 2 lineage. We also detected subgroup F rabies virus. This information should be useful for development of mass vaccination campaigns for dogs and eventual large-scale control programs in this country.
APPLICATION OF LOCAL BINARY PATTERN AND PRINCIPAL COMPONENT ANALYSIS FOR FACE RECOGNITION

Recognizing facial expressions of human beings by a computer is an interesting and challenging problem. Facial feature extraction consists in localizing the most characteristic face components such as eyes, nose, and mouth regions within the face images that portray the human faces. In this paper, combination of Local Binary Pattern (LBP) and Principal Component Analysis (PCA) is presented. LBP code is used as texture descriptor of the face image.LBP is used for their tolerance against different facial expressions, different lighting conditions. The eyes and nose region is extracted from the LBP face image. PCA is used for dimension reduction of the feature vector.The complete system has been tested on the standard Olivetti Research Laboratory (ORL) databasesof people under different facial expressions. Keywords—Principal Component Analysis, Face Recognition, Local Binary Pattern
The Ukrainian Voter: Electoral Behavior in a New Democracy

The “normalization” of politics in new democracies is an important concern of political science research. Normalization could refer to democratic consolidation when democracy “becomes the only game in town” (Linz and Stepan 1996). Some of the factors contributing to normalization are stable institutions, the rule of law, and transparency in power transfer, among others. Yet, it can be argued that the democratic process is normalized when programmatic parties compete for political office by wooing a sophisticated and knowledgeable electorate (Kitschelt 1992, 1995, 2000). This inquiry is a story of such normalization in the case of a new post-communist democracy – Ukraine. In the literature the Ukrainian public is depicted as highly apolitical, unsophisticated, and divided along the ethno-cultural regional cleavage which contributes to the problems of normalization of electoral competition. Moreover, there is a general sense that voters are “the least likely segment of Ukrainian polity" to influence political processes (Copsey 2005). Yet, the events of the Orange Revolutions showed otherwise. It does not seem reasonable any longer to ignore the Ukrainian voter and her role in the development of a democratic Ukraine. Recently Timothy J. Colton (2011) lamented the lack of the individual level analysis of Ukrainian electorate. This study is a decisive attempt to remedy this oversight. Using the survey data from International Foundation for Electoral Studies (IFES) from 1994, 1997 -2008 I develop and analyze a model of the sophisticated voter in the new democracy. I argue that over time, as voters have more experience with democratic processes, they learn how to properly link their own preferences with appropriate parties and candidates, relying on numerous factors including, but not limited to, the ethno-cultural and socioeconomic attributes, such factors as evaluation of the political leaders and issues are also instrumental in voter decision making. The results of this study have important implications for the study of Ukrainian politics and a broader literature on voting behavior. The curious case of the Ukrainian voter suggests a need to reexamine the theoretical and conceptual frameworks of democratic consolidation hypotheses as well as the developmental modes of electoral behavior.
Understanding the Variation in the Information Content of Earnings: A Return Decomposition Analysis

We use the Campbell (1991) return decomposition framework to reexamine the variation in the information content of earnings between profit firms and loss firms and over time. We show that current earnings surprises are more strongly correlated with the discount rate news component of returns for loss firms and in the recent period. This stronger correlation offsets the positive relation between current earnings surprises and the earnings news component of returns, causing the overall earnings-return relation to be weaker for loss firms and during the recent period. Consistent with these findings, we also find that discount rate news is a more important driver of the return variation of loss firms and in the recent period. Our results highlight the importance of time-varying discount rates for understanding the information content of earnings.
Base station sleeping and power control for bursty traffic in cellular networks

In this paper, we study sleeping and power control of a single-cell cellular network with bursty traffic. The base station (BS) sleeps whenever the system is empty, and wakes up when N users are assembled. The service capacity of the BS in the active mode is controlled through its transmitting power. The total power consumption and average delay for bursty traffic that follows the Interrupted Poisson Process (IPP) are analyzed. We discuss when the BS should sleep and the impact of traffic burstiness on it. The impact of the sleeping threshold and the transmitting power on the system performance is also investigated. The numerical results show that given the average traffic load, the more bursty the traffic is, the less the total power is consumed, while the delay performance of the more bursty traffic is better only under certain circumstances.
Minimal distortion 3-D watermarking using statistics of geodesic distances

This paper describes a statistical 3-D digital watermarking method using distributions of distances measured along mesh surfaces. The proposed method employs a mesh propagation procedure called the Fast Marching Method (FMM), which defines regions of equal geodesic distance width calculated with respect to a reference location on the mesh surface. The embedding is performed by statistically changing the normalized distribution of local geodesic distances. Vertices are moved onto the plane of triangles containing the current geodesic front line as generated by the FMM. Such vertex perturbations ensure that the resulting distortions in the 3-D graphics is minimal.
A Systematic Review of Model Based Testing Tool Support

Model-based testing (MBT) is about testing a software system by using a model of its behaviour. To benefit fully from MBT, automation support is required. This paper presents a systematic review of prominent MBT tool support where we focus on tools that rely on state-based models. The systematic review protocol precisely describes the scope of the search and the steps involved in tool selection. Precisely defined criteria are used to compare selected tools and comprise support for test coverage criteria, level of automation for various testing activities, and support for the construction of test scaffolding. The results of this review should be of interest to a wide range of stakeholders: software companies interested in selecting the most appropriate MBT tool for their needs; organizations willing to invest into creating MBT tool support; researchers interested in setting research directions.
Developing electronic government success models for G2C and G2B scenarios

This study aims to develop models for studying e-government success using variables from theory and test them empirically. The first part of this research is to develop generic and theoretical models for e-Government success for G2C (Government-to-Citizen) and G2B (Government-to-Business) environments using case studies of best practices from UAE and other countries and existing literature on e-Government and Information Systems success. The second part of the study then aims to validate the developed models using real world data collected through surveys. This study will be the first to develop such a comprehensive model as there are no models at present examining e-government success specifically. Furthermore, the need for comprehensive models for e-Government success and the available theory to support the proposed models also should result in successful outcome of this study.
‘Learning the rules of the game’: emotional labor and the gendered academic subject in the United States

Abstract In this article, we investigate how entrenched sexism in higher education can take root in graduate school, where many of us learn the ‘rules of the academic game’ through our roles as teaching assistants (TAs). Feminist and anti-racist scholars have documented how these ‘rules of the game’ are scripted on different academic bodies. We focus this article on the stubborn persistence of sexism in university life through the everyday, mundane forms of emotional labor and care that TAs feel obligated to perform. As the current #MeToo movement reminds us, sexism, sexist exploitation, and oppression are as evident today as they were decades ago when feminist scholars and activists challenged the masculinism of geographical discourse through examinations of power, knowledge, and subjectivity. Our research returns to these themes by examining TAs’ experiences of sexism in the classroom through the lens of critical care ethics. A focus on TAs brings attention to the constitution of the gendered academic subject and identifies the emotional labor required to manage this subject. We believe that the durability of sexism warrants an investigation of the sites where women learn their ‘place’ in the academy.
Virtual Cluster Head-set based Avalanche Predication in Himalayan region

Environmental disasters are most of the time unpredictable and occur within short spans of time. Therefore we have to develop technology to capture relevant signals with minimum monitoring delay. The Himalaya, the longest chain of mountains in the world, shows complex variations in snow and meteorological conditions as one traverse from east to west and from south to north. Wireless Sensor Networks (WSNs) systems have potential to provide raw data for environmental science such as Avalanche Predication. WSN mainly consists of large number of sensor nodes with limited power supply which are densely deployed in physical environment. Once the battery is drain-out sensor node is considered as a dead node sensor and thus can't longer participate in the working of wireless sensor network and we can say whole the network is dead. In order to prolong the network life time, an energy efficient sensor network needed, so by using different clustering techniques we can get an energy efficient WSNs. In this paper we extend the LEACH protocol by using a Virtual Cluster Head-set (VCH) instead of a cluster head. The main goal of this paper is to detect snowfall induced avalanche which occur commonly in Western Himalayan region of India using WSNs.
Improved K-Means clustering technique using distance determination approach

Powerful systems for collecting data and managing it in large databases are in place in all large and mid-range organizations. The value of raw data (collected over a long time) is on the ability to extract high-level information: information useful for decision support, for exploration, and for better understanding of the phenomena generating the data. Traditionally this task of extracting information was done with the help of analysis where one or more analysts with the help of statistical techniques provide summaries and generate reports. Such an approach fails as the volume and dimensionality of the data increase. Hence tools to aid the automation of analysis tasks are becoming a necessity. Thus, data mining was evolved which is “automatic”: extraction of patterns of information from data. Clustering, the grouping of the objects of a database into meaningful subclasses such that similarity of objects in the same group is maximized and similarity of objects in different groups is minimized, is called clustering But my focus is on partitioning methods only , and proposing a new clustering algorithm for automatic discovery of data clusters
The MIT vision machine

Computer vision has developed algorithms for several early vision processes, such as edge detection, stereopsis, motion, texture, and color, which give separate cues as to the distance from the viewer of three-dimensional surfaces, their shape, and their material properties. Biological vision systems, however, greatly outperform computer vision programs. I t is clear that one of the keys to the reliability, flexibility, and robustness of biological vision system in unconstrained environments is their ability to integrate many diEerent visual cues. For this reason, we continue the development of a Vision Machine system to explore the issue of intagration of early vision modules. The s m a h serves the purpose of developing parallel vision algorithms, because its main computational engine is a parallel superwmputer, the Connection Machine.
Transverse Plane Motion at the Ankle Joint

The ankle is often considered to have little or no capacity to move in the transverse plane. This is clear in the persistent concept that it is the role of the subtalar joint to accommodate the transverse plane motion of the leg while the foot remains in a fixed transverse plane position on the floor. We present data from noninvasive in vivo study of the ankle subtalar complex during standing internal and external rotation of the leg and study of the ankle subtalar complex during walking. These data reinforce the results of cadaver study and invasive in vivo study of the ankle/subtalar complex. We suggest that the ankle is capable of considerable movement in the transverse plane (generally greater than 15 degrees) and that its role in the mechanism that allows the foot to remain in a fixed transverse plane position on the floor while the leg rotates in the transverse plane, is not simply the transfer of the transverse plane moment to the subtalar joint, but is accommodation of some of the necessary movement.
Multi-relational Topic Model for Social Recommendation

Various attribute and relation information is used in social recommendation systems. However, previous approaches fail to use them in a unified way. In this paper, we propose a unified framework for social recommendation. Entities like users and items are described by their tags. We model each entity using topic models like Latent Dirichlet Allocation(LDA) and then connect these topic models to form a multi-relational network. Various relations between entities in recommender systems such as rating relation or user friend relation can be expressed as edges in the multi-relational network. We evaluate our model on a real-life dataset collected from a commercial recommender website. Experiments validate the generative performance and predictive performance of our model.
Image Searching by Events with Deep Learning for NTCIR-12 Lifelog

We construct a automatically system to participate Lifelog task in NTCIR-12 that find the image out correctly by events. In our system, We have employed deep learning method to approach the targets. In our processing, we use stanford parser and named-entities recognition method to process text of events. Also, we employ word to vector toolkit to transfer words to vectors.Moreover, we construct a model ,training it with word2vec, to calculate the correlation be-tween each search task and image. By using this model, we find relevant images from every task in this topic.
Specific bovine antibody response against a new recombinant Cryptosporidium parvum antigen containing 4 zinc-finger motifs.

A Cryptosporidium parvum sporozoite and oocyst lambda gt11 cDNA library was screened with a hyperimmune rabbit serum that was developed against insoluble fragments of ultrasonicated oocysts. A clone named Cp22.4. 1 encoding a protein of 231 amino acids with 4 zinc-finger domains characterized by a Cys-X2-Cys-X4-His-X4-Cys motif was isolated and characterized. There was a complete match between the sequencing data of the coding region of Cp22.4. 1 and the corresponding gene at chromosomal level. Cloning in a pBAD-TOPO-TA expression vector permitted to evaluate the antigenicity of the recombinant His-tagged antigen. This antigen was recognized by 2 out of 5 sera from Cryptosporidium immune calves and not by sera from parasite naive animals.
A Hamiltonian-Preserving Scheme for the Liouville Equation of Geometrical Optics with Partial Transmissions and Reflections

We construct a class of Hamiltonian-preserving numerical schemes for the Liouville equation of geometrical optics, with partial transmissions and reflections. This equation arises in the high frequency limit of the linear wave equation, with a discontinuous index of refraction. In our previous work [Hamiltonian-preserving schemes for the Liouville equation of geometrical optics with discontinuous local wave speeds, J. Comput. Phys. 214 (2006), pp. 672-697], we introduced the Hamiltonian-preserving schemes for the same equation when only complete transmissions or reflections occur at the interfaces. These schemes are extended in this paper to the general case of partial transmissions and reflections. The key idea is to build into the numerical flux the behavior of waves at the interface, namely, partial transmissions and reflections that satisfy Snell’s law of refraction with the correct transmission and reflection coefficients. This scheme allows a hyperbolic stability condition, under which positivity, and stabilities in both $l^1$ and $l^\infty$ norms, are established. Numerical experiments are carried out to study the numerical accuracy.
3D quantification of facial edemas

This work presents a procedure for the 3D quantification of facial edemas. This issue is instrumental for assessing the effectiveness of specific drugs and/or surgical provisions in facial surgery. The considered problems are the automatic acquisition of face masks of adequate precision, the registration of the 3D masks of the same patient taken at different times during the edema evolution and the estimate of the volume characterizing the edema.
Magnifying Meditation’s Benefits: On Interoceptive Attention among Healthy Older Adults

This study used a sample of novice, older adult meditators to test the significance of interoceptive attention to nasal respiratory sensation on the degree of magnification of the effects of meditation. A randomized controlled study was conducted with healthy older adults ( N =4). Compared to an active control condition, nasal breathing participants showed an increase in mindfulness as reported with higher total scores on the post-Mindful Awareness Attention Scale (MAAS). Participants in the intentional nasal breathing group reported an increase in overall awareness of cognitive functioning and holistic interoception during daily activities- indicating the statistical significance of increased dispositional mindfulness when paired with intentional nasal breathing. Now more than ever, as our global population of older adults continues to increase, we need to bridge conversations about working memory and executive decision making as functions of mindfulness, magnifying effects of nasal breathing on limbic neuronic stimulation, as well as demonstrating effects extending to older adults. These three findings have important implications for the development of novel therapeutic approaches with people who experience cognitive impairment and such approaches lend themselves to potential reductions in health care costs.
Decentral Item-Based Collaborative Filtering for Recommending Images on Mobile Devices

Decentral recommender systems appear well suited for mobile scenarios, but have not been investigated thoroughly or implemented very much so far. We have designed and implemented a system to recommend images on Personal Digital Assistants (PDAs). Our approach also incorporates recommending for groups of users that are present at a public shared display. The system exchanges rating vectors among PDAs, computes local matrices of item similarity and utilizes them to generate recommendations. Our innovation in comparison to existing systems includes improving the extensibility of the data model by introducing versioned rating vectors. In addition, we have optimized the storage requirements on the mobile device. We have evaluated the approach in a small user study. Furthermore, the scalability of our system was analyzed using a standard recommender data set resulting in positive findings.