Miracle-dz/UniFAR-FTUs huggingface dataset:
Hypoxia Inducible Factor-1 # in Astrocytes-and / or Myeloid Cells is not Required for the Development of Autoimmune Demyelinating Disease Cell-Specific Roles of HIF-1 # in EAE

This work was supported by a National Multiple Sclerosis Society postdoctoral fellowship to N.L. M. and NIH/ NINDS grants R01NS051470 and R01NS052189 to K.A. V.A. R is an American Heart Association (AHA) postdoctoral fellow and D.D. holds Scientist Development Grant 13SDG17210051 from AHA. The J. David Gladstone Institutes received support from a National Center for Research Resources (grant RR18928).
Acute Pulmonary Embolectomy: A Contemporary Approach

Background—Acute pulmonary embolism confers a high mortality rate despite advances in diagnosis and therapy. Thrombolysis is often effective but has a high frequency of major bleeding complications, especially intracranial hemorrhage. Therefore, we liberalized our criteria for acute pulmonary embolectomy and considered operating on patients with anatomically extensive pulmonary embolism and concomitant moderate to severe right ventricular dysfunction despite preserved systemic arterial pressure. Methods and Results—We report 29 (17 men and 12 women) consecutive patients who underwent embolectomy from October 1999 through October 2001. Twenty-six patients (89%) survived surgery and were alive more than 1 month postoperatively. Median follow-up is 10 months. Conclusion—The high survival rate of 89% can be attributed to improved surgical technique, rapid diagnosis and triage, and careful patient selection. We hope that other tertiary centers will evaluate pulmonary embolism patients with an algorithm that includes surgical embolectomy as one of several therapeutic options. Our contemporary approach to pulmonary embolectomy no longer confines this operation to a treatment of last resort reserved for clinically desperate circumstances.
Navigating the early career years: Barriers and strategies for young adults with disabilities

BACKGROUND: Young adults with disabilities in their early career years face limited access to high wage/high skill jobs, barriers in the workplace, and inadequate opportunities for career retention and advancement. OBJECTIVE: The purpose of this literature review was to examine the process of career development for young adults with disabilities entering the workforce and document strategies for vocational rehabilitation counselors to facilitate career advancement. MATERIALS AND METHODS: A literature search was conducted using the online databases Academic Search Premier, ERIC, and PsychInfo. Key words for the search included the terms: disabilities, emerging adulthood, young adults, career advancement, vocational development, and early career. Articles included in this review met the following criteria: (a) published in peer reviewed journals in or after the year 2000, (b) findings addressed either processes, barriers, or strategies for emerging adults with disabilities entering the workforce. RESULTS: Major barriers to career advancement include: a) lack of work experience and restricted aspirations, b) sporadic patterns of early employment, c) limited access to postsecondary education and training, and d) discrimination and prejudice in the workforce. Strategies to enhance early career development included: a) developing individual attributes and skills, b) broadening the range of careers explored, c) creating initial work experience opportunities, d) obtaining postsecondary education/training, e) providing supports to facilitate advancement on the job, and f) advocating for changes in the workplace. CONCLUSIONS: Using an ecological framework to impact individual skills, create training opportunities, and enhance work place environments, rehabilitation counselors can help young adults with disabilities gain equal access to career options and ultimately achieve economic independence and stability.
Tumor and Stem Cell Biology PGC 1 a Promotes Tumor Growth by Inducing Gene Expression Programs Supporting Lipogenesis

Despite the role of aerobic glycolysis in cancer, recent studies highlight the importance of themitochondria and biosynthetic pathways as well. PPARg coactivator 1a (PGC1a) is a key transcriptional regulator of several metabolic pathways including oxidative metabolism and lipogenesis. Initial studies suggested that PGC1a expression is reduced in tumors compared with adjacent normal tissue. Paradoxically, other studies show that PGC1a is associated with cancer cell proliferation. Therefore, the role of PGC1a in cancer and especially carcinogenesis is unclear. Using Pgc1a / and Pgc1aþ/þ mice, we show that loss of PGC1a protects mice from azoxymethane-induced colon carcinogenesis. Similarly, diethylnitrosamine-induced liver carcinogenesis is reduced in Pgc1a / mice as compared with Pgc1aþ/þ mice. Xenograft studies using gain and loss of PGC1a expression showed that PGC1a also promotes tumor growth. Interestingly, while PGC1a induced oxidative phosphorylation and tricarboxylic acid cycle gene expression, we also observed an increase in the expression of two genes required for de novo fatty acid synthesis, ACC and FASN. In addition, SLC25A1 and ACLY, which are required for the conversion of glucose into acetyl-CoA for fatty acid synthesis, were also increased by PGC1a, thus linking the oxidative and lipogenic functions of PGC1a. Indeed, using stable C isotope tracer analysis, we show that PGC1a increased de novo lipogenesis. Importantly, inhibition of fatty acid synthesis blunted these progrowth effects of PGC1a. In conclusion, these studies show for the first time that loss of PGC1a protects against carcinogenesis and that PGC1a coordinately regulates mitochondrial and fatty acid metabolism to promote tumor growth. Cancer Res; 71(21); 6888–98. 2011 AACR.
Technology and knowledge document cluster analysis for enterprise R&D strategic planning

Through technology and knowledge document analysis, companies can realise the condition of specified technology development and the potential competitors in the market. As patents provide exclusive right and legal protection for patent inventors, patents play an important role in the development of technology. This paper presents the process of patent knowledge extraction and methodologies of patent analysis to improve the efficiency of patent analysis. Furthermore, the methodologies proposed in this paper include patent map analysis, patent technology clustering, patent document clustering and technology maturity measurement. Through these methodologies, companies can gain rich information and perform better in patent management. Moreover, the strategic plans of R&D can also be determined using the methodologies proposed in this paper.
Critical assessment of methods of protein structure prediction—Round VII

This paper is an introduction to the supplemental issue of the journal PROTEINS, dedicated to the seventh CASP experiment to assess the state of the art in protein structure prediction. The paper describes the conduct of the experiment, the categories of prediction included, and outlines the evaluation and assessment procedures. Highlights are improvements in model accuracy relative to that obtainable from knowledge of a single best template structure; convergence of the accuracy of models produced by automatic servers toward that produced by human modeling teams; the emergence of methods for predicting the quality of models; and rapidly increasing practical applications of the methods. Proteins 2007. © 2007 Wiley‐Liss, Inc.
Meta-analysis of randomized controlled comparisons of psychopharmacological and psychological treatments for anxiety disorders

Background. A number of meta-analyses have led to contradictory results regarding the efficacy of the psychological and pharmacological treatment of anxiety disorders. The main reasons for these inconsistent results seem to be the inclusion of heterogeneous studies and influences of selection biases. We performed a meta-analysis, which only included studies using a direct comparison of pharmacological, psychological, or combined treatments. Method. Sixteen studies on panic disorder, six studies on social anxiety disorder, and two studies on generalized anxiety disorder have been analyzed. Effect sizes for differences between the different treatment modalities were calculated. Also, the effect sizes of the pre–post differences were calculated. Results. Pharmacological treatment, cognitive-behavioural treatment, and the combination of both treatment modalities all led to substantial improvement between pre- and post-treatment. Combined pharmacological and psychological treatment was superior to the monotherapies for panic disorder. For social anxiety disorder, there is only preliminary support for combined treatment. Due to lack of sufficient data, no final conclusions can be drawn for generalized anxiety disorder. Conclusions. While drug treatment and CBT showed equal efficacy, only in panic disorder the combination of pharmacological and psychological treatment was superior to either treatment alone. For the other anxiety disorders, the evidence for greater efficacy of combination treatment is still not sufficient due to lack of studies.
What Motivates a Lifelong Learner?

Lifelong learners are people who display an attitude and ability that prompts them to learn across their life spans. Even in the testing environment of United States schools today, a goal of library media specialists is to help children become lifelong learners. The Self-Determination Theory (SDT, Deci & Ryan, 1985) provides a framework for examining a positive disposition toward learning, or the motivation to learn: the key attribute of a lifelong learner. Additional areas explored include contributions of school library research toward an understanding of student motivation, suggestions for further areas of study, and implications for school libraries.
User Modelling for Digital Libraries: A Data Mining Approach

Abstract i User Modelling for Digital Libraries: A Data Mining Approach Enrique Frias-Martinez Abstract Digital libraries provide information services for users who have diverse needs. Personalised digital libraries, constructed using a user-guided approach in which users need to state their preferences explicitly, have been proposed as a way to meet the needs of different users. The problems of using this approach are that users may not be aware of their preferences and that human factors are ignored. To address these problems, this thesis investigates an automatic approach that captures user preferences with data mining techniques and identifies relevant human factors for personalisation. More specifically, this thesis aims to study to which extent data mining can identify user preferences and to clarify the role of human factors in determining user behaviour and user perception. In addition to studying the modelling capabilities of different individual data mining techniques, including K-means, Hierarchical Clustering and Fuzzy Clustering, Robust Clustering is applied for grouping user behaviour and user perception due to its capabilities of handling the inherent fuzziness of human data. The created clusters are used to find relationships with a number of human factors in order to identify their role in determining user behaviour and user perception. The results show that there are relationships between cognitive styles and user behaviour. In addition, there are links between the levels of experience and user perception. However, novices do not show a homogenous perception so the levels of experience may not be suitable for personalisation. In other words, cognitive style has been considered as the main relevant human factor for personalisation, in which an adaptive interface is developed and compared with an interface that includes adaptability with the user-guided approach. The purpose of this comparison is to demonstrate to which extent data mining can capture user preferences. The results show that data mining is able to identify user preferences to such an extent that the inclusion of adaptability for personalisation does not increase user satisfaction. In summary, this thesis makes contributions to three communities: digital libraries, data mining and personalisation. For the digital library community, this thesis has showed that cognitive style is the main relevant human factor that influences user behaviour in a digital library. Based on the results, an adaptive interface is developed to accommodate the needs of each cognitive style. For the data mining community, this thesis has indicated that data mining can be successfully used to identify user preferences. In particular, Robust Clustering is an effective technique to capture and model user behaviour and user perception. For the personalisation community, this thesis has demonstrated that personalisation has positive influences on the increase of user satisifaction.
Predictors of PTSD symptoms for criterion A and non-criterion A events

This study evaluated the current DSM-IV conceptualization of posttraumatic stress disorder (PTSD). It examined predictors (i.e., event, person, and cognitive characteristics) and the factor structure of PTSD symptoms for events that do and do not meet criterion A. Event, person, and cognitive variables included in this study explained 47% of the variance in PTSD symptoms for the criterion A group and 56% of the variance in PTSD symptoms for the noncriterion A group. In both groups, cognitive variables explained the majority of variance in PTSD symptom severity. Although predictors of PTSD symptoms varied for criterion A and non-qualifying events, the factor structure was similar, suggesting that trauma responses to nonqualifying events may look very similar to trauma responses to criterion A events. This study suggests that a reevaluation of the diagnostic criteria for PTSD is warranted. Predictors of PTSD Symptoms iii Acknowledgements I would like to thank Dr. Dean Lauterbach for his mentoring and direction that proved invaluable to this project. I also thank my committee members, Drs. Norman Gordon, Ellen Koch, and Lisa Lauterbach. I appreciate their expertise, time, and effort that were invested in this project. I would like to thank my undergraduate research assistants who helped at numerous stages during this project. Thank you, Alexander Upham, Melissa Butler, Bruce Pych, Julia Krahnke, Joe Mihelich, and Nicolette Westveer for your enthusiasm and energy during the data collection process. I could not have asked for more conscientious and talented research assistants. Finally, I appreciate all of the psychology instructors and professors who encouraged their students to participate in my study and all the student participants who made this study possible. Predictors of PTSD Symptoms iv TABLE OF CONTENTS Page ABSTRACT ii ACKNOWLEDGEMENTS iii TABLE OF CONTENTS iv LIST OF FIGURES vi LIST OF TABLES vii TABLE OF ABBREVIATIONS viii ii ACKNOWLEDGEMENTS iii TABLE OF CONTENTS iv LIST OF FIGURES vi LIST OF TABLES vii TABLE OF ABBREVIATIONS viii SECTIONS
USING SEMANTIC CUES FOR CONTEXTUAL RECOMMENDATION

Recommender systems help users overcome the information overload problem and have been widely used in an ever-increasing number of e-commerce websites. However, most existing recommender systems use simplistic user model. In this paper, we describe how context can be brought to bear on recommender systems. We propose a new approach to integrating user rating vectors with a contextual retrieval cue to generate recommendations. We use a user model consisting of short and long term memory with context playing the role of retrieval and we use semantic information extracted from the domain knowledge as the key cue for distinguishing user context. An evaluation of our recommendation algorithm was carried out using Movielens data by extending standard collaborating filtering algorithm using semantic cues.
The Engineering and Initial Results of a Transformable Low-cost High-Resolution PET Camera

We have developed a high-resolution transformable positron emission tomography (PET) camera that can be configured into either a whole-body mode (83-cm detector ring diameter, 13-cm axial field-of-view (AFOV)) or a brain/breast/axilla (54-cm detector ring diameter, 21-cm AFOV) mode. The camera has 12 rectangular detector modules, and the detector gap between adjacent modules is very small and remains constant for each configuration. Each module has a large detection area (13 cm times 21 cm) and 38016 bismuth germanate (BGO) detector crystals of 2.7 times 2.7 times 18 mm3 with built-in front-end electronics. To improve spatial sampling, the gantry on which the camera is mounted can be rotated 30deg with a fine step size of 1deg, and the high-speed electronics and detector modules also rotate along with the gantry. This system uses only 924 photomultiplier tubes (PMT) by applying a low-cost high-resolution PMT-quadrant-sharing detector design. To compensate for the slower scintillation timing of BGO detectors, the camera is equipped with the "HYPER", high-yield pile-up event recovery front-end electronics. A fast light-emitting diode (LED) cross-reference PMT tuning method is used to maintain the PMT gain balance. The system has been constructed and tested for preliminary imaging characteristics. The system sensitivity is 4.2% for whole-body and 9.2% for brain/breast/axilla mode measured with Na-22 at center of field of view (FOV). For brain/breast/axilla modes, the transaxial image resolutions at 0 and 10 cm were found to be 2.7 and 4.0 mm, respectively, while for whole-body mode, the image resolutions were 3.3 and 3.9 mm. The slice thickness resolution ranged from 2.6 to 3.3 mm for middle 7 detector rings in brain/breast/axilla modes. High quality Hoffman brain phantom images were obtained in both brain and whole-body modes.
Combining symbolic and corpus-based approaches for the generation of successful referring expressions

We present an approach to the generation of referring expressions (REs) which computes the unique RE that it predicts to be fastest for the hearer to resolve. The system operates by learning a maximum entropy model for referential success from a corpus and using the model's weights as costs in a metric planning problem. Our system outperforms the baselines both on predicted RE success and on similarity to human-produced successful REs. A task-based evaluation in the context of the GIVE-2.5 Challenge on Generating Instructions in Virtual Environments verifies the higher RE success scores of the system.
Examining Korean American Parent-Child Relationships Through Bilingual Language Use

Many Korean American (KA) families live at the intersection of two languages and two cultures. When considering how parent-child relationships are negotiated through daily interactions within perceived parameters of cultural norms and expectations, it becomes important to better understand which cultural norms and expectations are taken up by different family members who have access to different sets of cultural norms. Through the lens of positioning theory, this study analyzed home interactions of three KA families with children (ages 6–12) to investigate the relationship between bilingual use and parent-child roles. Parent-child interactions demonstrated complex negotiations around boundaries of parents’ authority through language shifts between Korean and English and speech-level shifts between formal and informal language in Korean. Family members displayed linguistic strategies that either broke away from traditionally hierarchical parent-child relationships by moving toward more friend-like horizontal relationships or reinforced expectations and norms associated with roles in the family. Findings illuminate changing patterns in norms and expectations of modern KA family relations.
Manifold Relevance Determination

In this paper we present a fully Bayesian latent variable model which exploits conditional nonlinear (in)-dependence structures to learn an efficient latent representation. The latent space is factorized to represent shared and private information from multiple views of the data. In contrast to previous approaches, we introduce a relaxation to the discrete segmentation and allow for a "softly" shared latent space. Further, Bayesian techniques allow us to automatically estimate the dimensionality of the latent spaces. The model is capable of capturing structure underlying extremely high dimensional spaces. This is illustrated by modelling unprocessed images with tenths of thousands of pixels. This also allows us to directly generate novel images from the trained model by sampling from the discovered latent spaces. We also demonstrate the model by prediction of human pose in an ambiguous setting. Our Bayesian framework allows us to perform disambiguation in a principled manner by including latent space priors which incorporate the dynamic nature of the data.
Acupuncture for enhancing early recovery of bowel function in cancer

Background: Cancer patients undergoing surgical procedure often suffer from bowel dysfunction and postoperative ileus (POI). Cancer management for early recovery of bowel function is still a challenging topic. Acupuncture has been commonly used in a variety of gastrointestinal diseases. The aim of this study is to evaluate the effects of acupuncture therapy to reduce the duration of POI and enhance bowel function in cancer patients. Methods: We will systematically screen all randomized controlled trials (RCTs) published through electronically and hand searching. The following search engines including Medline, EMBASE, Cochrane CENTRAL, the Cumulative Index to Nursing and Allied Health Literature, Allied and Complementary Medicine Database, the Chinese Biomedical Literature Database, the China National Knowledge Infrastructure, VIP Information, Wanfang Data, one Japanese database (Japan Science and Technology Information Aggregator, Electronic) and 2 Korean Medical Databases (Korean Studies Information, and Data Base Periodical Information Academic) will be retrieved. Supplementary sources will be searched including gray literature, conference proceedings, and potential identified publications. Two reviewers will independently conduct the trial inclusion, data extraction and assess the quality of studies. The time to first passing flatus and time to first bowel motion will be assessed as the primary outcomes. Adverse effects, time to first bowel sound, visual analog scale (VAS) pain score, hospital stay, and postoperative analgesic requirement will be measured as secondary outcomes. Methodological quality will be evaluated according to the Cochrane risk of bias. Details of interventions will be assessed by the Standards for Reporting Interventions in Controlled Trials of Acupuncture (STRICTA) checklist. All analyses will be applied by RevMan (version 5.3) and StataSE (version 12). Ethics and Dissemination: This systematic review will provide up-to-date information on acupuncture therapy for early recovery of bowel function in cancer patients. This review does not require ethical approval and will be reported in a peer-reviewed journal and presented at a relevant conference. Trial Registration Number: PROSPERO CRD42016049633.