Miracle-dz/UniFAR-FTUs huggingface dataset:
Overexpression of the Nuclear Receptor Coactivator AIB1 (SRC-3) during Progression of Pancreatic Adenocarcinoma

Purpose: The nuclear receptor coactivator amplified in breast cancer 1 (AIB1) was found to be amplified and overexpressed in breast and some other epithelial tumors. We have reported that expression of AIB1 is rate limiting for growth factor, as well as hormone signaling. Here, we assess the involvement of AIB1 in the development of pancreatic adenocarcinoma. Experimental Design: We investigated expression levels of AIB1 protein and mRNA in pancreatic cancer cell lines and in a series of archival pancreatic adenocarcinoma (n = 78), pancreatic intraepithelial neoplasia (n = 93), pancreatitis (n = 28), and normal pancreas tissues (n = 52). We also determined AIB1 gene copy numbers by fluorescence in situ hybridization in a subset of cases. Results: In normal pancreas ducts, we rarely found detectable levels of AIB1 mRNA or protein (<6% of the samples). In pancreatitis and low-grade intraepithelial neoplasia, we found an increased frequency of AIB1 expression (>14 and >23%, respectively) relative to normal tissues (P < 0.01). Adenocarcinoma, as well as high-grade intraepithelial neoplasia, showed increased levels as well as the highest frequency of AIB1 expression with >65% of samples positive for mRNA and protein (P < 0.0001 relative to the other groups). An increased copy number of the AIB1 gene, observed in 37% of cancers, may account for a portion of the increase in expression. Conclusions: AIB1 overexpression is frequent in pancreatic adenocarcinoma and its precursor lesions. On the basis of its rate-limiting role for the modulation of growth factor signals, we propose a major role of AIB1 in the multistage progression of pancreatic cancer.
Validation of regional climate model simulation with observational data over Bangladesh

Abbreviations CHAPTER 1: INTRODUCTION 1.0 Introduction 1.1 Geographical Description of Bangladesh 1.2 Climate Characteristics of Bangladesh 1.2.1 Temperature 1.2.2 Rainfall 1.3 Objectives and scope of the present work CHAPTER 2: RegCM MODEL 2.0 Introduction ofRegCM Model 2.1 The Frame Work ofRegCM Model 2.2 Model Description 2.2.1 Dynamics 2.3 Physics 2.3.1 Land Surface Model 2.3.2 Planetary Boundary Layer Scheme 2.3.3 Convective Precipitation Schemes 2.3.3.1 Grell Scheme 2.3.3.2. Kuo Scheme 2.3.3.3 Betts.Miller Scheme CHAPTER3: DATA USED AND METHOLOGY 3.1 Data Used 3.2ICBC 3.2.1 Sea Surface Temperature 3.2.2 Initial and Boundary Conditions 3.3 Observed Meteorological Data 3.4 Methodology Pages
Transdiaphragmatic pressure and neural respiratory drive measured during inspiratory muscle training in stable patients with chronic obstructive pulmonary disease

Purpose Inspiratory muscle training (IMT) is a rehabilitation therapy for stable patients with COPD. However, its therapeutic effect remains undefined due to the unclear nature of diaphragmatic mobilization during IMT. Diaphragmatic mobilization, represented by transdiaphragmatic pressure (Pdi), and neural respiratory drive, expressed as the corrected root mean square (RMS) of the diaphragmatic electromyogram (EMGdi), both provide vital information to select the proper IMT device and loads in COPD, therefore contributing to the curative effect of IMT. Pdi and RMS of EMGdi (RMSdi%) were measured and compared during inspiratory resistive training and threshold load training in stable patients with COPD. Patients and methods Pdi and neural respiratory drive were measured continuously during inspiratory resistive training and threshold load training in 12 stable patients with COPD (forced expiratory volume in 1 s ± SD was 26.1%±10.2% predicted). Results Pdi was significantly higher during high-intensity threshold load training (91.46±17.24 cmH2O) than during inspiratory resistive training (27.24±6.13 cmH2O) in stable patients with COPD, with P<0.01 for each. Significant difference was also found in RMSdi% between high-intensity threshold load training and inspiratory resistive training (69.98%±16.78% vs 17.26%±14.65%, P<0.01). Conclusion We concluded that threshold load training shows greater mobilization of Pdi and neural respiratory drive than inspiratory resistive training in stable patients with COPD.
Predictive control of three-level DC/AC inverter fed PMSM with torque ripple minimization and constant switching frequency

The presented DTC-3V-3L method was designed to ensure the high performance of PMSM drive. Using the predictive approach the algorithm minimizes torque ripples, ensures constant switching frequency and DC link voltage balancing. Moreover, it also provides the fastest dynamic torque response, similar to the fastest non-linear methods.
u NOISE DETECTION AND ELIMINATION IN DATA PREPROCESSING : EXPERIMENTS IN MEDICAL DOMAINS

This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, redistribution , reselling , loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. Compression measures used in inductive learners, such as measures based on the minimum description length principle, can be used as a basis for grading candidate hypotheses. Compression± based induction is suited also for handling noisy data. T his paper shows that a simple compression measure can be used to detect noisy training examples, where noise is due to random classication errors. A technique is proposed in which noisy examples are detected and eliminated from the training set, and a hypothesis is then built from the set of remaining examples. T his noise elimination method was applied to preprocess data for four machine± learning algorithms, and evaluated on selected medical domains.
Adenosine-5'-Triphosphate (ATP) Protects Mice against Bacterial Infection by Activation of the NLRP3 Inflammasome

It has been established that Adenosine-5'-triphosphate (ATP) can activate the NLRP3 inflammasome. However, the physiological effect of extracellular ATP on NLRP3 inflammasome activation has not yet been investigated. In the present study, we found that ATP was indeed released during bacterial infection. By using a murine peritonitis model, we also found that ATP promotes the fight against bacterial infection in mice. ATP induced the secretion of IL-1β and chemokines by murine bone marrow-derived macrophages in vitro. Furthermore, the intraperitoneal injection of ATP elevated the levels of IL-1β and chemokines in the mouse peritoneal lavage. Neutrophils were rapidly recruited to the peritoneum after ATP injection. In addition, the effects on cytokine and chemokine secretion and neutrophil recruitment were markedly attenuated by the pre-administration of the caspase-1 inhibitor Ac-YVAD-cho. Ac-YVAD-cho also significantly attenuated the protective effect of ATP against bacterial infection. In the present study, we demonstrated a protective role for ATP during bacterial infection and this effect was related to NLRP3 inflammasome activation. Together, these results suggest a role for ATP in initiating the immune response in hosts suffering from infections.
Non-Complexing Anions for Quantitative Speciation Studies Using Raman Spectroscopy in Fused Silica High-Pressure Optical Cells under Hydrothermal Conditions

This paper reports methods for obtaining time-dependent reduced isotropic Raman spectra of aqueous species in quartz capillary high-pressure optical cells under hydrothermal conditions, as a means of determining quantitative speciation in hydrothermal fluids. The methods have been used to determine relative Raman scattering coefficients and to examine the thermal decomposition kinetics of the non-complexing anions bisulfate (HSO4−), perchlorate (CIO4−), perrhenate (ReO4−), and trifluoromethanesulfonate, or “triflate” (CF3SO3−) in acidic and neutral solutions at temperatures up to 400 °C and 30 MPa. Arrhenius expressions for calculating the thermal decomposition rate constants are also reported. Thermal stabilities in the acidic solutions followed the order HSO4− (stable) > ReO4− > CIO4− > CF3SO3− with half-lives (t1/2) > 7 h at 300 °C. In neutral solutions, the order was HSO4− (stable) > CF3SO3− > ReO4− > CIO4−, with t1/2 > 8 h at 350 °C. CF3SO3− was extremely stable in neutral solutions, with t1/2 > 11 h at 400 °C.
A Distributed Memory Unstructured Gauss-Seidel Algorithm for Multigrid Smoothers

Gauss-Seidel is a popular multigrid smoother as it is provably optimal on structured grids and exhibits superior performance on unstructured grids. Gauss-Seidel is not used to our knowledge on distributed memory machines as it is not obvious how to parallelize it effectively. We, among others, have found that Krylov solvers preconditioned with Jacobi, block Jacobi or overlapped Schwarz are effective on unstructured problems. Gauss-Seidel does however have some attractive properties, namely: fast convergence, no global communication (ie, no dot products) and fewer . ops per iteration as one can incorporate an initial guess naturally. This paper discusses an algorithm for parallelizing Gauss-Seidel for distributed memory computers for use as a multigrid smoother and compares its performance with preconditioned conjugate gradients on unstructured linear elasticity problems with up to 76 million degrees of freedom.
Meta-analysis of the Association between HLA-DRB1 Allele and Rheumatoid Arthritis Susceptibility in Asian Populations

The aims of this study were to summarize results on the association of HLA-DRB1 with rheumatoid arthritis (RA) in Asians and to determine if the shared epitope (SE) hypothesis could explain the meta-analysis results. Among the papers published between January 1987 and July 2006 on RA susceptibility in Asian-Mongoloid populations (Korean, Japanese, Chinese, and Thai), 12 were selected for the meta-analysis. Mongoloid-Asian patients with RA had significantly higher frequencies of HLA-DRB1*0101, *0401, *0410, and *1001 than controls (OR 1.5-2.1, p<0.05 for association). When analyses were restricted to more ethnically homogeneous populations, HLA-DRB1*0405 showed a significant susceptibility to RA in Koreans (OR 5.65, 95% CI 4.32-7.39), whereas the HLA-DRB1*0301, *0403, *0406, *0701, *1301, and *1405 alleles showed protective association with RA (OR 0.32-0.70, p<0.05 for association). In conclusion, it was found that HLA-DRB1 *0101, *0401, *0405, *0410, and *1001 are susceptible, while HLA-DRB1*0301, *0403, *0406, *0701, *1301, and *1405 are protective in Asian-Mongoloids. All the RA-associated alleles except DRB1*0301 could be explained by the structural model supporting the SE hypothesis that RA susceptibility is determined by the combination of amino acid residues at HLA-DR β71 and β74, not by β71 alone.
Impact of reionization on CMB polarization tests of slow-roll inflation

Estimates of inflationary parameters from the CMB B-mode polarization spectrum on the largest scales depend on knowledge of the reionization history, especially at low tensor-to-scalar ratio. Assuming an incorrect reionization history in the analysis of such polarization data can strongly bias the inflationary parameters. One consequence is that the single-field slow-roll consistency relation between the tensor-to-scalar ratio and tensor tilt might be excluded with high significance even if this relation holds in reality. We explain the origin of the bias and present case studies with various tensor amplitudes and noise characteristics. A more model-independent approach can account for uncertainties about reionization, and we show that parametrizing the reionization history by a set of its principal components with respect to E-mode polarization removes the bias in inflationary parameter measurement with little degradation in precision.
UNED at iCLEF 2008: Analysis of a Large Log of Multilingual Image Searches in Flickr

In this paper, we summarise our analysis of the large log of multilingual image searches in Flickr provided to iCLEF 2008 participants. We have studied (a) correlations between the language skills of searchers in the target language and other session parameters, such as success (was the image found? ), number of query refinements, etc.; (b) learning eects over time; (c) usage of specific cross-language search facilities and (d) users perceptions on the task (questionnaire analysis). We have identified 5101 complete search sessions (searcher/target image pairs) in the logs provided by the organisation. Our analysis shows that when users have active competence in the target language, their success rate is 12% higher than if they do not know the language at all. If the user has passive competence of the language (i.e. can partially understand texts but cannot make queries), the success rate equals those with active competence, but at the expense of executing more interactions with the system.
Constraints as Prior Knowledge

Making complex decisions in real world problems often involves assigning values to sets of interdependent variables where an expressive dependency structure among these can influence, or even dictate, what assignments are possible. Commonly used models typically ignore expressive dependencies since the traditional way of incorporating non-local dependencies is inefficient and hence lead to expensive training and inference. This paper presents Constrained Conditional Models (CCMs), a framework that augments probabilistic models with declarative constraints as a way to support decisions in an expressive output space while maintaining modularity and tractability of training. We develop, analyze and compare novel algorithms for training and inference with CCMs. Our main experimental study exhibits the advantage our framework provides when declarative constraints are used in the context of supervised and semi-supervised training of a probabilistic model.
Optimizing and scheduling of super large-scale seawater reverse osmosis desalination system

In order to realize optimizing and scheduling of super large-scale seawater reverse osmosis (SWRO) desalination system, an optimizing-scheduling system based on General Algebraic Modeling System (GAMS) is developed according to the forecast of water consumption. Firstly, water consumption in each period of a day was forecasted based on historical water consumption data. Secondly, an optimizing-scheduling model with the minimum energy consumption cost as the target was developed based on the process technological requirements and period-based tariff policy of SWRO desalination system. Finally, the optimizing solution was made for the model by using GAMS software. It is indicated from the scheduling example that the scheduling system can be used to realize optimizing and scheduling successfully and obtain obvious economic and social benefits.
Therapy for Fibrotic Diseases: Nearing the Starting Line

An emerging consensus indicates that fibrotic diseases in lung, liver, and kidney exhibit common underlying mechanisms, which can be targeted therapeutically. Fibrosis, the accumulation of excess extracellular matrix in injured tissue, is the final common pathway for numerous diseases, including many of the lung, liver, kidney, and skin. This State of the Art Review outlines an emerging consensus that these diseases have many underlying features in common. The authors further describe ongoing efforts to develop effective therapies, including a discussion of obstacles to progress. Fibrosis, or the accumulation of extracellular matrix molecules that make up scar tissue, is a common feature of chronic tissue injury. Pulmonary fibrosis, renal fibrosis, and hepatic cirrhosis are among the more common fibrotic diseases, which in aggregate represent a huge unmet clinical need. New appreciation of the common features of fibrosis that are conserved among tissues has led to a clearer understanding of how epithelial injury provokes dysregulation of cell differentiation, signaling, and protein secretion. At the same time, discovery of tissue-specific features of fibrogenesis, combined with insights about genetic regulation of fibrosis, has laid the groundwork for biomarker discovery and validation, and the rational identification of mechanism-based antifibrotic drugs. Together, these advances herald an era of sustained focus on translating the biology of fibrosis into meaningful improvements in quality and length of life in patients with chronic fibrosing diseases.
Deployment morbidity among search-and-rescue dogs used after the September 11, 2001, terrorist attacks.

OBJECTIVES To determine characteristics, variables associated with deployment morbidity, and injuries and illnesses of search-and-rescue dogs associated with the Sept 11, 2001, terrorist attacks. DESIGN Historical cohort study. ANIMALS 96 dogs. PROCEDURE Data collected included previous medical or surgical history, physical attributes of dogs, type and number of years of training, site of deployment, shift and hours worked, and number of days deployed. Combined morbidity was defined as 1 or more abnormalities of body systems, including traumatic injuries. RESULTS Handlers of 96 of the 212 dogs responded to the surveys. Fifty-nine dogs were deployed by the Federal Emergency Management Agency, 10 by police forces, and 27 as members of other search-and-rescue teams. Sixty-five dogs (incidence rate, 17 events/1,000 dog search hours) had combined morbidity during deployment. System-specific morbidity rates included gastrointestinal tract signs (5 events/1,000 dog search hours), cuts and abrasions mostly on the feet (5 events/1,000 dog search hours), fatigue (6 events/1,000 dog search hours), change in appetite (6 events/1,000 dogs search hours), dehydration (5 events/1,000 dog search hours), respiratory tract problems (2 events/1,000 dog search hours), heat exhaustion (2 events/1,000 dog search hours), and orthopedic or back problems (2 events/1,000 dog search hours). Dogs deployed to the World Trade Center were 6.6 times more likely to have combined morbidity, compared with dogs at the Pentagon. CONCLUSIONS AND CLINICAL RELEVANCE Injury and illnesses occurred in most dogs and affected several organ systems, but all were minor.
Bipolar cascade superluminescent diodes at the 1.04μm wavelength regime

In this study, we investigate the performance of GaAs-based bipolar cascade superluminescent diodes with different cavity lengths. The device operates around the important bio-optical therapeutic 1.04-mum wavelength window. The introduction of tunnel junctions tends to minimize the nonuniform carrier distribution between distinct multiple quantum-wells (QWs), which is a problem in conventional SLDs, whose electroluminescent spectra are governed by the center wavelength of QWs near the p-side. Our devices exhibit nice electrical characteristics of low leakage current and overcome the limitation of nonuniform carrier distribution, thereby presenting a promising prospect for the near infrared white-light sources.
COMPRESSING THE DIGITAL LIBRARY

these two are in tension—data compression saves space, but at the expense of added access time; and indexing methods provide fast access, but usually at the expense of considerable amounts of additional storage space. Indeed, a complete index to a large body of text can be larger than the text itself—after all, it might store the location of every word in the text. The prospect of digital libraries presents the challenge of storing vast amounts of information efficiently and in a way that facilitates rapid search and retrieval. Storage space can be reduced by appropriate compression techniques, and searching can be enabled by constructing a full-text index. But these two requirements are in conflict: the need for decompression increases access time, and the need for an index increases space requirements. This paper resolves the conflict by showing how (a) large bodies of text can be compressed and indexed into less than half the space required by the original text alone, (b) full-text queries (Boolean or ranked) can be answered in small fractions of a second, and (c) documents can be decoded at the rate of approximately one megabyte a second. Moreover, a document database can be compressed and indexed at the rate of several hundred megabytes an hour. This paper shows that it is possible to make compression and indexing work together efficiently. We describe compression methods suited to large amounts of text that allow both random-access decoding of individual documents and fast execution; we show how the index can itself be compressed so that only a small amount of overhead space is required to store it; and we show how the application of compression techniques allows efficient construction of the index in the first instance. The result is a system that can take a large body of text, and convert it to a compressed text and index that together take up less than half the space occupied by the original data. Combining the two techniques incurs little penalty in access speed—in fact, the access speed can even be improved, since there is less data to be read in from slow secondary storage devices. Moreover, the initial indexing and compression processes can be effected on a mid-range workstation at a rate of several hundred megabytes an hour.
Efficient implementation of packet pre-filtering for scalable analysis of IP traffic on high-speed lines

In this paper an efficient FPGA implementation of a packet pre-filtering algorithm based on Bloom filter is presented. In high speed link the traffic classification involves a very large amount of data per each packet processed. Both header and payload should be analyzed. This leads to use hardware with high computational power and very expensive, in order to support requirement of real-time classification. Our system, reducing the data flow sent to the classifier allows a realtime classification with reduced hardware resources.
HVS-DBS: human visual system-aware dynamic luminance backlight scaling for video streaming applications

Despite the advances in Liquid Crystal Display's (LCD) technology, LCD power consumption is still one of the major limiters of battery lifetime for handheld devices. The main contribution to LCD subsystem power consumption comes from the backlight. This can be substantially reduced by dynamically adapting backlight intensity while compensating the image quality degradation through image pixel transformation. Several compensation algorithms have been recently proposed to this purpose, but none of them is really capable of ensuring a target image quality while achieving major power savings. We propose a novel on-line technique for dynamic backlight scaling. Our approach is HVS (i.e. Human Visual System) and image structure-aware. We provide a fully operational implementation of the proposed framework by which we carried out a full characterization of the overall system power consumption versus QoS.
Ion Exchange in Environmental Processes: Fundamentals, Applications and Sustainable Technology

As environmental and energy related regulations have grown, ion exchange has assumed a dominant role in offering solutions to many concurrent problems both in the developed and the developing world. Written by an internationally acknowledged leader in ion exchange research and innovation, Ion Exchange: in Environmental Processes is both a comprehensive introduction to the science behind ion exchange and an expert assessment of the latest ion exchange technologies. Its purpose is to provide a valuable reference and learning tool for virtually anyone working in ion exchange or interested in becoming involved in that incredibly fertile field.