Cell cycle regulation of the cyclin A gene promoter is mediated by a variant E2F site.

Cyclin A is involved in the control of S phase and mitosis in mammalian cells. Expression of the cyclin A gene in nontransformed cells is characterized by repression of its promoter during the G1 phase of the cell cycle and its induction at S-phase entry. We show that this mode of regulation is mediated by the transcription factor E2F, which binds to a specific site in the cyclin A promoter. It differs from the prototype E2F site in nucleotide sequence and protein binding; it is bound by E2F complexes containing cyclin E and p107 but not pRB. Ectopic expression of cyclin D1 triggers premature activation of the cyclin A promoter by E2F, and this effect is blocked by the tumor suppressor protein p16INK4.

Guía de la juventud o Deberes que el niño ha de aprender para completar su instrucción /

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Uber die wanderungsfahikeit von saureresten in substituierten a...

Thesis (doctoral)--

The Blue Highway

The Blue Highway is a collection of eleven literary short stories and ten miniatures that depict men in trouble, searching for a code to live by. The miniatures are repressed memories, appearing suddenly like the tips of ice bergs and act as stepping stones (tension bridges) between the larger works. The stories begin at the end with "Time Out", the story of Frank, a down and out homeless vet at the end of his rope. Then we begin the journey along "The Blue Highway" with Danny and his gang of teenage bandits, taking themselves to Disney World to see if they can recapture their lost dream. On our journey we will meet Mark, the ex-killer, an old Cuban fisherman who will not give up his honor, a young man on a way to a war who discovers a fantastic treasure, a soldier on his way home again, two MP's who nearly kill the wrong man, we will spend a night on an African savannah with wild hyenas and finally, meet a grandfather who discovers the one gift which might save his family. The same gift which might save Frank as well. ^

The blue highway

The Blue Highway is a collection of eleven literary short stories and ten miniature that depict men in trouble, searching for a code to live by. The miniatures are repressed memories, appearing suddenly like the tips of ice bergs and act as stepping stones (tension bridges) between the larger works. The stories begin at the end with "Time Out", the story of Frank, a down and out homeless vet at the end of his rope. Then we begin the journey along "The Blue Highway" with Danny and his gang of teenage bandits, taking themselves to Disney World to see if they can recapture their lost dream. On our journey we will meet Mark, the ex-killer, an old Cuban fisherman who will not give up his honor, a young man on a way to a war who discovers a fantastic treasure, a soldier on his way home again, two MP's who nearly kill the wrong man, we will spend a night on an African savannah with wild hyenas and finally, meet a grandfather who discovers the one gift which might save his family. The same gift which might save Frank as well.

Measuring function and mobility among clients with diabetes in Samoa

The aim of the thesis was to collect baseline data and to investigating suitable physical tests and a self-rapport questionnaire. Collected data was used to find a routine measurement when investigating foot health, function and mobility among clients suffering from diabetes in Samoa. Twenty-one participants suffering from diabetes were included in the study. Clients answered the Foot function index (FFI) questionnaire and performed physical tests, consisting of Bergs balance scale (BBS) and Time up and go (TUG). Results from the physical tests revealed a great balance disturbance and mobility limitations among the majority of the clients. General high weight and BMI was measured among both genders. Subjects with the highest BMI performed lowest time during TUG test. The statistic analyze revealed a strong correlation between the two physical tests, indicating that one of the tests could be applied as a routine measurement in the future, when evaluating function and mobility in Samoa. The compilation of self-report questionnaires indicated a general good foot health with a low amount of pain, disabilities and activity limitations.

Datasets, features, learning, and models in visual recognition

Visual recognition is a fundamental research topic in computer vision. This dissertation explores datasets, features, learning, and models used for visual recognition. In order to train visual models and evaluate different recognition algorithms, this dissertation develops an approach to collect object image datasets on web pages using an analysis of text around the image and of image appearance. This method exploits established online knowledge resources (Wikipedia pages for text; Flickr and Caltech data sets for images). The resources provide rich text and object appearance information. This dissertation describes results on two datasets. The first is Berg’s collection of 10 animal categories; on this dataset, we significantly outperform previous approaches. On an additional set of 5 categories, experimental results show the effectiveness of the method. Images are represented as features for visual recognition. This dissertation introduces a text-based image feature and demonstrates that it consistently improves performance on hard object classification problems. The feature is built using an auxiliary dataset of images annotated with tags, downloaded from the Internet. Image tags are noisy. The method obtains the text features of an unannotated image from the tags of its k-nearest neighbors in this auxiliary collection. A visual classifier presented with an object viewed under novel circumstances (say, a new viewing direction) must rely on its visual examples. This text feature may not change, because the auxiliary dataset likely contains a similar picture. While the tags associated with images are noisy, they are more stable when appearance changes. The performance of this feature is tested using PASCAL VOC 2006 and 2007 datasets. This feature performs well; it consistently improves the performance of visual object classifiers, and is particularly effective when the training dataset is small. With more and more collected training data, computational cost becomes a bottleneck, especially when training sophisticated classifiers such as kernelized SVM. This dissertation proposes a fast training algorithm called Stochastic Intersection Kernel Machine (SIKMA). This proposed training method will be useful for many vision problems, as it can produce a kernel classifier that is more accurate than a linear classifier, and can be trained on tens of thousands of examples in two minutes. It processes training examples one by one in a sequence, so memory cost is no longer the bottleneck to process large scale datasets. This dissertation applies this approach to train classifiers of Flickr groups with many group training examples. The resulting Flickr group prediction scores can be used to measure image similarity between two images. Experimental results on the Corel dataset and a PASCAL VOC dataset show the learned Flickr features perform better on image matching, retrieval, and classification than conventional visual features. Visual models are usually trained to best separate positive and negative training examples. However, when recognizing a large number of object categories, there may not be enough training examples for most objects, due to the intrinsic long-tailed distribution of objects in the real world. This dissertation proposes an approach to use comparative object similarity. The key insight is that, given a set of object categories which are similar and a set of categories which are dissimilar, a good object model should respond more strongly to examples from similar categories than to examples from dissimilar categories. This dissertation develops a regularized kernel machine algorithm to use this category dependent similarity regularization. Experiments on hundreds of categories show that our method can make significant improvement for categories with few or even no positive examples.