Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential reactivity of two homogeneous LDL-cholesterol methods to LDL and VLDL subfractions, as demonstrated by ultracentrifugation and HPLC.

BACKGROUND The analytical and clinical performance of homogeneous LDL-cholesterol assays has been reported, but their reactions with subfractions of LDL and VLDL have not been described in detail. METHODS We evaluated reaction selectivity of two homogeneous LDL-cholesterol assays, LDLk (Kyowa Medex) and LDLd (Daiichi Pure Chemical), with ultracentrifugally isolated VLDL and LDL subfractions to identify the lipoprotein particles from which the cholesterol recognized by these assays originates. RESULTS The LDLd (y) and LDLk (x) methods correlated highly for whole serum samples: y = 0.986x - 39.5 mg/L (r = 0.966; n = 34). In isolated VLDL, the LDLk and the LDLd methods recovered 17.3% and 23.8% of cholesterol, respectively; but correlation analysis revealed differential reactivity to small and large VLDL particles. For the isolated LDL subfraction of density 1.019-1.040 kg/L, the LDLd method had significantly higher reactivity (95.6-98.7%) than the LDLk (88.4-92.0%). Both methods, however, demonstrated poor recovery (approximately 50%) for the 1.050-1.063 kg/L fraction, indicating incomplete reactivity with small, dense LDL. Reactivity with lipoprotein(a) was better (71.2-90.8%) for both methods than with small LDL. For intermediate-density lipoprotein (IDL), there was no significant difference in recovery between the two methods (71.7% for LDLk and 68.9% for LDLd), but the LDLk method appeared to be more sensitive to IDL particle size. CONCLUSIONS The two homogeneous assays for LDL-cholesterol demonstrate only partial reactivity to small, dense LDL and nonspecific reactions to VLDL particles. Modification will be required in the homogeneous methods to obtain LDL-cholesterol values equivalent to those obtained by ultracentrifugation.
Trafficking in Drug Users: Professional Exchange Networks in the Control of Deviance

Acknowledgements Introduction 1. The emergence of the 'drug problem': social change versus social control 2. Control systems from exchange in networks: towards a synthesis of system and action theory 3. Stratification in information and referral exchange 4. Exchange relationships in social-control system 5. The social system: boundary maintenance and hierarchical control 6. Summary: the control system in context Appendixes Notes Bibliography Name index Subject index.
Effects of Dietary Fat Intake on HDL Metabolism

High-density lipoprotein (HDL) is a lipoprotein which has anti-atherogenic property by reversing cholesterol transport from the peripheral tissues to liver. Low HDL-cholesterol (HDL-C) as well as high low-density lipoprotein-cholesterol (LDL-C) is associated with the development of coronary heart diseases (CHD). Various epidemiological studies have suggested that the development of CHD increase in individuals with less than 40 mg/dL of HDL-C. In spite of accumulation of evidences suggesting a significant association between low HDL-C and CHD, effects of dietary factors on HDL metabolism remained largely unknown. We reviewed published articles about effects of dietary fat intake on HDL metabolism. The substitution of fatty acids (FA) for carbohydrates is beneficially associated with HDL metabolism. Monounsaturated FA intake may not affect HDL-C. Trans-FA is significantly associated with reduction of HDL-C, and is also adversely related with total cholesterol/HDL-C. Fish oils consumption, especially docosahexaenoic acid consumption, may be favorably associated with HDL metabolism. Although plant sterols and stanols may not affect HDL-C, policosanol intake is associated with a clinically significant decrease in the LDL/HDL ratio.
Phenotypic Switching Induced by Damaged Matrix Is Associated with DNA Methyltransferase 3A (DNMT3A) Activity and Nuclear Localization in Smooth Muscle Cells (SMC)

Extracellular matrix changes are often crucial inciting events for fibroproliferative disease. Epigenetic changes, specifically DNA methylation, are critical factors underlying differentiated phenotypes. We examined the dependency of matrix-induced fibroproliferation and SMC phenotype on DNA methyltransferases. The cooperativity of matrix with growth factors, cell density and hypoxia was also examined. Primary rat visceral SMC of early passage (0–2) were plated on native collagen or damaged/heat-denatured collagen. Hypoxia was induced with 3% O2 (balanced 5% CO2 and 95% N2) over 48 hours. Inhibitors were applied 2–3 hours after cells were plated on matrix, or immediately before hypoxia. Cells were fixed and stained for DNMT3A and smooth muscle actin (SMA) or smooth muscle myosin heavy chain. Illumina 450 K array of CpG sites was performed on bisulfite-converted DNA from smooth muscle cells on damaged matrix vs native collagen. Matrix exquisitely regulates DNMT3A localization and expression, and influences differentiation in SMCs exposed to denatured matrix +/− hypoxia. Analysis of DNA methylation signatures showed that Matrix caused significant DNA methylation alterations in a discrete number of CpG sites proximal to genes related to SMC differentiation. Matrix has a profound effect on the regulation of SMC phenotype, which is associated with altered expression, localization of DNMTs and discrete changes DNA methylation.
A Two-Level Place Names Identification Based on the N-Shortest Path and CRFs

This paper presents a two-level place names identification method based on N-shortest path and Conditional Random Fields(CRFs) aiming at solving the low recall rate problem in Chinese place names identification. First, the rough segmentation method based on N-shortest path is used to improve the recall rate of Chinese place names identification at low level; Second, the result of rough segmentation is submitted to high level as one of the features of high-level place names identification. High level’ s CRFs model uses the feature which submitted by low level, single and complex features of place names words to tag the text. Adding the complex feature is conducive to mine the context information and improve accuracy rate of place names identification, and the result of text tagging could be combined with rules to identify place names finally. This two-level model ensures a high recall rate and improves the accuracy rate. During experiment, choose the mature corpora of People’ s Daily in January 1998 as training samples, which include 3128 place names(except duplicate names), and extract articles of People’ s Daily in 2003 randomly to carry out the test. Experimental results achieve a high recall rate, and this method is proved to be practical and effective.
Cost-Based Analysis of Hierarchical DHT Design

Flat DHT architectures have been the main focus of the research on DHT design so far. However, there have been also a number of works proposing hierarchical DHT organizations and pointing their advantages. They mostly rely on the intuitive understanding that hierarchy is desirable in any complex system. In this paper we formalize this intuition within a general cost-based framework. We provide a cost model of a specific hierarchical DHT organization composed of superpeers and leafnodes, and show that the costs of running the network are not necessarily minimized for flat DHT organization, providing thus a formal motivation for hierarchical DHTs. We further hint on what distributed algorithms can be applied in practice to reach optimal operating point of the network
Design of iterative ROI transmission tomography reconstruction procedures and image quality analysis.

PURPOSE An iterative edge-preserving CT reconstruction algorithm for high-resolution imaging of small regions of the field of view is investigated. It belongs to a family of region-of-interest reconstruction techniques in which a low-cost pilot reconstruction of the whole field of view is first performed and then used to deduce the contribution of the region of interest to the projection data. These projections are used for a high-resolution reconstruction of the region of interest (ROI) using a regularized iterative algorithm, resulting in significant computational savings. This paper examines how the technique by which the pilot reconstruction of the full field of view is obtained affects the total runtime and the image quality in the region of interest. METHODS Previous contributions to the literature have each focused on a single approach for the pilot reconstruction. In this paper, two such approaches are compared: the filtered backprojection and a low-resolution regularized iterative reconstruction method. ROI reconstructions are compared in terms of image quality and computational cost over simulated and physical phantom (Catphan600) studies, in order to assess the compromises that most impact the quality of the ROI reconstruction. RESULTS With the simulated phantom, new artifacts that appear in the ROI images are caused by significant errors in the pilot reconstruction. These errors include excessive coarseness of the pilot image grid and beam-hardening artifacts. With the Catphan600 phantom, differences in the imaging model of the scanner and that of the iterative reconstruction algorithm cause dark border artifacts in the ROI images. CONCLUSIONS Inexpensive pilot reconstruction techniques (analytical algorithms, very-coarse-grid penalized likelihood) are practical choices in many common cases. However, they may yield background images altered by edge degradation or beam hardening, inducing projection inconsistency in the data used for ROI reconstruction. The ROI images thus have significant streak and speckle artifacts, which adversely affect the resolution-to-noise compromise. In these cases, edge-preserving penalized-likelihood methods on not-too-coarse image grids prove to be more robust and provide the best ROI image quality.
Exact and Approximate Algorithms for the Optimization of Area and Delay in Multiple Constant Multiplications

The main contribution of this paper is an exact common subexpression elimination algorithm for the optimum sharing of partial terms in multiple constant multiplications (MCMs). We model this problem as a Boolean network that covers all possible partial terms that may be used to generate the set of coefficients in the MCM instance. We cast this problem into a 0-1 integer linear programming (ILP) by requiring that the single output of this network is asserted while minimizing the number of gates representing operations in the MCM implementation that evaluate to one. A satisfiability (SAT)-based 0-1 ILP solver is used to obtain the exact solution. We argue that for many real problems, the size of the problem is within the capabilities of current SAT solvers. Because performance is often a primary design parameter, we describe how this algorithm can be modified to target the minimum area solution under a user-specified delay constraint. Additionally, we propose an approximate algorithm based on the exact approach with extremely competitive results. We have applied these algorithms on the design of digital filters and present a comprehensive set of results that evaluate ours and existing approximation schemes against exact solutions under different number representations and using different SAT solvers.
Global-scale Seismic Interferometry: Numerical Validation of the Acoustic Correlation Integral

Summary Applying seismic reflection imaging on a global scale is hard due to the (locally) sparse source distribution. We approach this problem with seismic interferometry (SI). In this paper, we derive an expression for global-scale SI and test it on a simplified 2D acoustic lossless Earth model. When we use responses from sources placed all around the model, we can reconstruct the full and multiple-free response due to a simulated source at one of the receiver positions. When we miss the responses from near-oset sources, we can still reconstruct the full Green’s function. We currently investigate which events in the Green’s function we can still reconstruct properly when responses from sources in the mid- and far-oset range are missing.
Build Smart Campus Using Human Behavioral Data

Recently, many research works have been done as a part of smart city research. As a miniature of a city, a university campus is a appropriate environment for kinds of research on smart city. One practical project named smart campus has been built in the University of Science, Technology of China(USTC) since the year of 2012. In this project, several smart campus systems are built based on human behavioral data analysis, they are providing many personal, useful services for students in their daily life. The systems are also used by university administrators to make some positive social impacts. In this paper, the methods to build some main functions in those systems are proposed. In addition, some research issues including privacy-preserving, incentive mechanism are also discussed.
Pilot Feedback Equalization for Time Varying OFDM Systems

It is well known that feedback and power loading can enhance the error rate performance (or link quality) of orthogonal frequency-division multiplexing (OFDM) systems. Conventional power loading algorithms for OFDM are based on forward channel state information (CSI) knowledge in the transmitter provided by a dedicated feedback link from the receiver. In this paper, we propose a feedback scheme where instead of providing the transmitter with forward-link CSI we directly send the received pilots back to the transmitter. The transmitter extracts the forward-link CSI, and compensates both the amplitude and the phase of the channel for each tone before transmitting the OFDM symbol, a process also known as pre-equalization. Although the proposed scheme is sub-optimum in terms of power loading, we show that our feedback technique converts the Rayleigh fading channel into a flat channel and also simplifies the receiver.
Localized adaptive learning of Mixture of Gaussians models for background extraction

The Mixture of Gaussians (MoG) background subtraction model is one of the most popular methods for segmenting moving objects in videos. However, to achieve satisfactory background subtraction results, its parameters need to be hand-tuned specifically for each scenario. This becomes a major obstacle for this model to be employed in real-time applications. This paper proposes a self-adaptive method for tuning of the parameters of Mixture of Gaussians (MoG) background model based on the local intensity changes. To cope with different motion patterns in different regions of a video frames, we have introduced a local parameters for each pixel in the frame. The robustness of the proposed method is tested on a variety of complex data-sets. It can be seen from the result that, despite its simplicity, the proposed model has achieved significant improvements compared to the standard model.
Neuro-Immune Abnormalities in Autism and Their Relationship with the Environment: A Variable Insult Model for Autism

Autism spectrum disorder (ASD) is a heterogeneous condition affecting an individual’s ability to communicate and socialize and often presents with repetitive movements or behaviors. It tends to be severe with less than 10% achieving independent living with a marked variation in the progression of the condition. To date, the literature supports a multifactorial model with the largest, most detailed twin study demonstrating strong environmental contribution to the development of the condition. Here, we present a brief review of the neurological, immunological, and autonomic abnormalities in ASD focusing on the causative roles of environmental agents and abnormal gut microbiota. We present a working hypothesis attempting to bring together the influence of environment on the abnormal neurological, immunological, and neuroimmunological functions and we explain in brief how such pathophysiology can lead to, and/or exacerbate ASD symptomatology. At present, there is a lack of consistent findings relating to the neurobiology of autism. Whilst we postulate such variable findings may reflect the marked heterogeneity in clinical presentation and as such the variable findings may be of pathophysiological relevance, more research into the neurobiology of autism is necessary before establishing a working hypothesis. Both the literature review and hypothesis presented here explore possible neurobiological explanations with an emphasis of environmental etiologies and are presented with this bias.
A Meme-Based Architecture for Modeling Creativity

This research is a collaborative work between a visual artist, a computer scientist, and a cognitive scientist, and focuses on the creative process involved in connecting two pictures by painting another picture in the middle. This technique was involved in four Inﬁnite Landscape workshops conducted at Art Museums in Japan and Europe over the last ﬁve years. Based on the artist’s verbal recollection of the ideas that occurred to him as he drew each of the connecting pictures, we identify the micro-processes underlying these ideas, and propose a meme-based, evolutionary-inspired architecture for modeling them.
A New Sample of Low-Mass Black Holes in Active Galaxies

We present an expanded sample of low-mass black holes (BHs) found in galactic nuclei. Using standard virial mass techniques to estimate BH masses, we select from the Fourth Data Release of the Sloan Digital Sky Survey all broad-line active galaxies with masses <2 × 106 M☉. BHs in this mass regime provide unique tests of the relationship between BHs and galaxies, since their late-type galaxy hosts do not necessarily contain classical bulges. Furthermore, they provide observational analogs of primordial seed BHs and are expected, when merging, to provide strong gravitational signals for future detectors such as LISA. From our preliminary sample of 19, we have increased the total sample by an order of magnitude to 174, as well as an additional 55 (less secure) candidates. The sample has a median BH mass of ⟨MBH⟩ = 1.3 × 106 M☉, and in general the objects are radiating at high fractions of their Eddington limits. We investigate the broad spectral properties of the sample; 55 are detected by ROSAT, with soft X-ray luminosities in the range 1040 to 7 × 1043 ergs s-1. Much like the preliminary sample, these objects are predominantly radio-quiet (R ≡ f6cm/f4400Å < 10), but 11 objects are detected at 20 cm, with radio powers (1021-1023 W Hz-1) that may arise from either star formation or nuclear activity; only 1% of the sample is radio-loud. We further confirm that, with ⟨Mg⟩ = -19.3 and ⟨g - r⟩ = 0.7 mag, the host galaxies are low-mass, late-type systems. At least 40% show disklike morphologies, and the combination of host galaxy colors and higher order Balmer absorption lines indicate intermediate-age stellar populations in a subset of the sample.
A Model of Balance-of-Payments Crises Due to External Shocks: Monetary vs. Fiscal Approaches

This paper develops a model for balance-of-payments (BOP) crises triggered by an external shock. Whether an external shock induces a BOP crisis depends crucially on the sequence of policy actions taken by the government's monetary and fiscal authorities. If the fiscal authority moves first and imposes an exogenous constraint on the monetary authority, an external shock can lead to a BOP crisis. However, if the monetary authority moves first and imposes an exogenous constraint on the fiscal authority, the same shock does not cause a BOP crisis.
On the approximation of Markov chains to determine the probability of extinction of a genotype

As it is known a precise definition of the Brownian motion involves a measure on the path space, such that it is possible to put the Brownian motion on a firm mathematical foundation. In this paper we refer to an application of asymptotic theory of stochastic differential equations in mathematical genetics. The construction of the Brownian motion as a limit of a rescaled random walk can be generalized to a class of Markov chains.
AUTOMATIC TERM RECOGNITION

This report presents the results of the initial research and study has been done for the project. It contains a discussion about the wider context of the project and the related work to the subject studied, as well as analysis of the specifications of the tool which will be constructed during the project. In particular, a brief introduction about ‘Text mining’ is provided, providing information about the history of the subject area, examples of applications that use Text Mining and a list of related subject areas. Then, the ‘Automatic Term Recognition’ (ATR) field is discussed, presenting some techniques used for ATR and focusing on the C/NC-Value (hybrid) method. Furthermore, the report contains a detailed presentation of the aims of the program and analysis of the method that will be used to develop it. In addition, the criteria of success are identified among with the evaluation methods will be used to test the program. Finally, the project plan is presented showing the deliverables and the deadlines, giving a clear view of all initial estimations.
Role of anti-glycoproteins D (anti-gD) and K (anti-gK) IgGs in pathology of herpes stromal keratitis in humans.

PURPOSE To assess the relative impact of antibodies specific for HSV-1 glycoproteins on eye disease in response to HSV-1 infection, the composition of antibodies specific for 10 of the viral glycoproteins, and the effect of anti-glycoprotein (g)D and anti-gK antibodies on antibody-dependent enhancement (ADE). METHODS In a prospective case-control study, sera from patients with a history of herpes stromal keratitis (HSK) were compared with sera from nonocular HSV-1-seropositive and HSV-seronegative control subjects. HSV-1 neutralizing antibody titer and type-specific IgG and IgM were measured. In addition, the presence of anti-HSV-1 gD and gK antibodies in the sera of all patients also was determined by ELISA using gD and gK antigens. Finally, the role of anti-gD- and gK-specific antibodies to ADE was investigated. RESULTS Average neutralizing antibody titers and levels of HSV-1 IgG were similar between HSK- and non-HSK-seropositive patients. However, the contribution of gD to the neutralizing antibody titer in HSK sera was significantly lower than that in non-HSK-seropositive patients, despite higher anti-gD ELISA titers. Overall, sera from patients with HSK had higher anti-gK antibody titers and induced ADE in vitro compared with non-HSK or seronegative sera. The ADE response in HSK sera was attributed to anti-gK antibody. CONCLUSIONS These results suggest that sera from HSK patients had higher anti-gD and -gK antibody titers than sera from seropositive patients who had no history of HSK despite similar levels of neutralizing antibody titers and HSV-1 IgG, that HSK sera induced ADE whereas sera from non-HSK patients did not induce ADE, and that anti-gD antibody in sera of HSK patients contributed less to the HSV-1 neutralization antibody titer than did sera from non-HSK patients.
Learning in Real Time: Theory and Empirical Evidence from the Term Structure of Survey Forecasts

We develop a theoretical framework for understanding how agents form expectations about economic variables with a partially predictable component. Our model incorporates the effect of measurement errors and heterogeneity in individual forecasters' prior beliefs and their information signals and also accounts for agents' learning in real time about past, current and future values of economic variables. We use the model to develop insights into the term structure of forecast errors, and test its implications on a data set comprising survey forecasts of annual GDP growth and inflation with horizons ranging from 1 to 24 months. The model is found to closely match the term structure of forecast errors for consensus beliefs and is able to replicate the cross-sectional dispersion in forecasts of GDP growth but not for inflation - the latter appearing to be too high in the data at short horizons. Our analysis also suggests that agents systematically underestimated the persistent component of GDP growth but overestimated it for inflation during most of the 1990s.