Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of sensitive and specific age- and gender-specific low-density lipoprotein cholesterol cutoffs for diagnosis of first-degree relatives with familial hypercholesterolaemia in cascade testing

Abstract Background: The plasma total and low-density lipoprotein-cholesterol (LDL-C) levels that are used as diagnostic criteria for familial hypercholesterolaemia (FH) probands in the general population are too stringent for use in relatives, given the higher prior probability of a first-degree relative being FH (50% vs. 1/500). Our objective was therefore to develop more appropriate LDL-C cutoffs to identify “affected” first-degree relatives found by cascade testing, to test their accuracy and utility in case identification, and to compare them with the published “Make early diagnosis to prevent disease” (MEDPED) cutoffs from the US. Methods: Using a large, anonymised sample of genetically tested first-degree relatives of Netherlands FH probands (mutation carriers/non-carriers, n=825/2469), age- and gender-specific LDL-C diagnostic cutoffs for first-degree relatives were constructed. These were used to test similar data from Denmark (n=160/161) and Norway (n=374/742). Results: Gender-specific LDL-C diagnostic cutoffs were established for six different age groups, which achieved an overall accuracy (measured as Youden's index) of 0.53 in the Netherlands data, and performed significantly better amongst younger (<25 years) compared to older first-degree relatives (0.68 vs. 0.42 Youden's index, p<0.001). Compared with the Netherlands data, age- and gender-adjusted mean LDL-C levels were significantly higher (approximately 0.5 mmol/L) in the Denmark and Norway subjects for both mutation carriers and non-carriers. After adjusting for this difference, the LDL-C cut-offs showed a similar accuracy in identifying mutation carriers from Denmark (81%, range 78%–86%) and Norway (84%, range 82%–86%). Although the MEDPED cutoffs performed significantly worse than these for the Netherlands data (p<0.001), they performed equally well in overall accuracy for the Norwegian and Danish data, although the LDL-C cutoffs had a significantly higher sensitivity but lower specificity for all three countries. Conclusions: The cutoffs developed here are designed to give the greatest overall accuracy when testing relatives of FH patients in the absence of a genetic diagnosis. They have a more balanced specificity and sensitivity than the MEDPED cutoffs that are designed to achieve higher specificity, which is more appropriate for cascade testing purposes. The data suggest that country-specific LDL-C cutoffs may lead to greater accuracy for identifying FH patients, but should be used with caution and only when a genetic diagnosis (DNA) is not available. Clin Chem Lab Med 2008;46:791–803.
Teacher Beliefs About the Outcomes of High-Stakes Testing and Measurement-Driven Instruction in Virginia's Public Schools

ii DEDICATION iii ACKNOWLEDGEMENTS iv LIST OF TABLES vii LIST OF FIGURES viii LIST OF EXHIBITS . ix CHAPTER 1 THE PROBLEM 1 The Quest for Accountability 1 Purpose of the Study 12 Research Question 12 Theoretical Model 12 Definitions 13 Personal Bias 15 Limitations 15 Summary of Chapter One and Overview of the Dissertation 16 CHAPTER 2 REVIEW OF RELATED LITERATURE 18 Outcomes for Students 18 Outcomes for Instructional Practices 21 Outcomes for Schools 24 Outcomes for Public Confidence in Teachers and Schools . 25 Outcomes for Teachers 26 Individual Research Studies 28 Summary . 60 CHAPTER 3 METHODOLOGY 63 Population . 63 Selection of Sample 63 Instrumentation and Data Collection Procedures 64 Analysis of Survey Data 70 Construction of Teacher Interview Protocol 71 Selection of Participants for Interviews 74 Administration of Interviews 75 Analysis of Interview Data 75
Competence Classification of Cumulus and Granulosa Cell Transcriptome in Embryos Matched by Morphology and Female Age

Objective By focussing on differences in the mural granulosa cell (MGC) and cumulus cell (CC) transcriptomes from follicles resulting in competent (live birth) and non-competent (no pregnancy) oocytes the study aims on defining a competence classifier expression profile in the two cellular compartments. Design: A case-control study. Setting: University based facilities for clinical services and research. Patients: MGC and CC samples from 60 women undergoing IVF treatment following the long GnRH-agonist protocol were collected. Samples from 16 oocytes where live birth was achieved and 16 age- and embryo morphology matched incompetent oocytes were included in the study. Methods MGC and CC were isolated immediately after oocyte retrieval. From the 16 competent and non-competent follicles, mRNA was extracted and expression profile generated on the Human Gene 1.0 ST Affymetrix array. Live birth prediction analysis using machine learning algorithms (support vector machines) with performance estimation by leave-one-out cross validation and independent validation on an external data set. Results We defined a signature of 30 genes expressed in CC predictive of live birth. This live birth prediction model had an accuracy of 81%, a sensitivity of 0.83, a specificity of 0.80, a positive predictive value of 0.77, and a negative predictive value of 0.86. Receiver operating characteristic analysis found an area under the curve of 0.86, significantly greater than random chance. When applied on 3 external data sets with the end-point outcome measure of blastocyst formation, the signature resulted in 62%, 75% and 88% accuracy, respectively. The genes in the classifier are primarily connected to apoptosis and involvement in formation of extracellular matrix. We were not able to define a robust MGC classifier signature that could classify live birth with accuracy above random chance level. Conclusion We have developed a cumulus cell classifier, which showed a promising performance on external data. This suggests that the gene signature at least partly include genes that relates to competence in the developing blastocyst.
Sky Segmentation Approach to obstacle avoidance

The capability to visually discern possible obstacles from the sky would be a valuable asset to a UAV for avoiding both other flying vehicles and static obstacles in its environment. The main contribution of this article is the presentation of a feasible approach to obstacle avoidance based on the segmentation of camera images into sky and non-sky regions. The approach is named the Sky Segmentation Approach (SSA). The central concept is that potentially threatening static obstacles protrude from the horizon line. The main challenge for SSA is automatically interpreting the images robustly enough for use in various environments and fast enough for real-time performance. In order to achieve robust image segmentation, machine learning is applied to a large database of images with many different types of skies. From these images, different types of visual features are extracted, among which most of the features investigated in the literature. In the interest of execution speed and comprehensibility, decision trees are learned to map the feature values at an image location to a classification as sky or non-sky. The learned decision trees are fast enough to allow real-time execution on a Digital Signal Processor: it is run onboard a small UAV at ∼ 30 Hz. Experiments in simulation and preliminary experiments on a small UAV show the potential of SSA for achieving robust obstacle avoidance in urban areas.
Commodity Futures in Asset Allocation

Commodity futures can supply fair investment return and unique diversification benefits to a portfolio manager. The relative performance between commodity futures and traditional financial assets is varied with business and market conditions. In general, commodity futures are negatively correlated with stocks and bonds. This negative correlation comes from the nature of the commodity market. Commodity futures can supply efficient diversification benefit to stocks and bonds investors when it is needed, i.e. when the stock or bond market displays poor performance or has a significant downside movement, commodity futures market usually shows strong performance and provides a good return. Both commodity futures and traditional financial assets display the structure break behavior and their risk/return characters change under different market and economic conditions. Markov regime-switching model can be applied to address this asset return dynamic and corresponding portfolio selection issue. The estimation results of a simple two-regime model support that for three risky asset classes there is a “normal” regime characterized by relatively high return and low risk and a “bad” regime characterized by relatively low return and high risk. An investment strategy ignoring the regime switching effect leads to inefficient asset allocation and poorer portfolio performance. When the market is in the “bad” regime, commodity futures perform relatively stronger than stocks and can provide more significant diversification benefit. Meanwhile, the regime-switching model can predict the break change of financial market and send signal to investors to increase commodity futures investment when financial market switches to the “bad” regime. A general regime-switching model extends the simple regime-switching model by using economic variables as instruments to predict asset returns. This model helps investigate asset return dynamics and optimal asset allocation under alternative economic environments. The first general regime switching model uses the short rate as the
Well-Being Tracking via Smartphone-Measured Activity and Sleep: Cohort Study

Background Automatically tracking mental well-being could facilitate personalization of treatments for mood disorders such as depression and bipolar disorder. Smartphones present a novel and ubiquitous opportunity to track individuals’ behavior and may be useful for inferring and automatically monitoring mental well-being. Objective The aim of this study was to assess the extent to which activity and sleep tracking with a smartphone can be used for monitoring individuals’ mental well-being. Methods A cohort of 106 individuals was recruited to install an app on their smartphone that would track their well-being with daily surveys and track their behavior with activity inferences from their phone’s accelerometer data. Of the participants recruited, 53 had sufficient data to infer activity and sleep measures. For this subset of individuals, we related measures of activity and sleep to the individuals’ well-being and used these measures to predict their well-being. Results We found that smartphone-measured approximations for daily physical activity were positively correlated with both mood (P=.004) and perceived energy level (P<.001). Sleep duration was positively correlated with mood (P=.02) but not energy. Our measure for sleep disturbance was not found to be significantly related to either mood or energy, which could imply too much noise in the measurement. Models predicting the well-being measures from the activity and sleep measures were found to be significantly better than naive baselines (P<.01), despite modest overall improvements. Conclusions Measures of activity and sleep inferred from smartphone activity were strongly related to and somewhat predictive of participants’ well-being. Whereas the improvement over naive models was modest, it reaffirms the importance of considering physical activity and sleep for predicting mood and for making automatic mood monitoring a reality.
Wetland mapping by using multi-band and multitemporal SAR images: A case study of Hong he National Natural Reserve

Wetland ecosystems have many important functions as the regional environment stabilization, natural species protection and ecological resources facility. Investigation and monitoring on wetland urgently need the application of remote sensing. The optional remote sensing technology is sometimes difficult to receive the data due to the bad weather, or in specific light conditions. However, radar remote sensing has a great potential for technical application in wetland mapping with its all-weather, all-time capabilities. And SAR scattering intensity is sensitive to the soil moisture of land cover and land change, therefore it is also helpful to the wetland research. In this paper, multi-band, multi-temporal SAR technique was used for wetland mapping. Unifies the SAR polarization characteristic, the backscattering characteristic of multi-temporal ENVISAT ASAR HH, HV, VV polarization data and ALOS PALSAR HH polarization data of different land use type and different vegetation type in Honghe National Natural Reserve (HNNR) were analyzed. The multi-temporal SAR data was used for vegetation classification research in decision tree classification method. And the authors use actual samples to do accuracy assessment in the way of computing confusion matrix. The result from this study shows that the improvement of water and marsh classification accuracy owes to the summer data, and the classification accuracy can be improved when we used the multitemporal data, HV polarization data in winter is more advantageous for forest map. The recognition rate of water, marsh and forest was relatively high. The classification of grass and bush had confusion. The classification accuracy of multitemporal SAR reached 79.55%.
Fears about treatment among young drug abusers in Hong Kong

Abstract This study examined fears about drug treatment among 300 young male heroin abusers in Hong Kong (172 newcomers and 128 repeaters) recruited from non-government treatment agencies. An indigenous 35-item Fears about Treatment Scale (Fears Scale) was developed to measure fears about treatment among the participants. Results showed that four factors (fear of failure, fear of labeling or disclosure, fear of maladaptation and fear of withdrawal) were abstracted from the scale. Reliability analyses showed that subscales based on these four factors and the total scale were internally consistent. The findings showed that treatment failure was the major fear in the respondents. The present findings suggest that drug treatment and rehabilitation services should help clients, particularly young substance abusers, mitigate their treatment fears.
Uncertainty and Density Forecasts of ARMA Models: Comparison of Asymptotic, Bayesian, and Bootstrap Procedures

The objective of this paper is to analyze the effects of uncertainty on density forecasts of stationary linear univariate ARMA models. We consider three specific sources of uncertainty: parameter estimation, error distribution, and lag order. Depending on the estimation sample size and the forecast horizon, each of these sources may have different effects. We consider asymptotic, Bayesian, and bootstrap procedures proposed to deal with uncertainty and compare their finite sample properties. The results are illustrated constructing fan charts for UK inflation.
Fundamental Indexing in Global Bond Markets: The Risk Exposure Explains It All

To investigate the fundamental indexing methodology, I apply it to global government bond markets and examine its exposure to several newly introduced risk factors. I find that the fundamental indexing approach outperforms a market-value-weighted index. However, my results show statistically significant and economically relevant exposures of fundamentally weighted indexes to the risk factors term and duration risk, default risk, convexity risk, liquidity risk, and carry trade risk. The increased risk exposure explains the outperformance of the fundamental indexing methodology in government bond markets.
Parent-therapist alliance in Family-Based Treatment for adolescents with anorexia nervosa.

OBJECTIVE This study aimed to describe the role of parent alliance in Family-Based Treatment (FBT) for adolescents with anorexia nervosa (AN). Differences between parent and child alliance with the therapist, mothers' and fathers' alliance, and their relationship to outcome were examined. METHOD Independent observers rated audiotapes of early therapy sessions to assess the therapeutic alliance of parents and adolescents with AN in FBT. Outcome was defined using a previously established cut-point for recovery from AN. RESULTS Mothers' and fathers' alliance scores with the therapist were similar and significantly higher than adolescent alliance scores early in treatment. Combined parent alliance did not predict recovery at the end of treatment. Difference in alliance scores between mothers and fathers, and parents and their child also did not predict recovery at the end of treatment. CONCLUSIONS In FBT, parents developed a strong alliance with the therapist early in treatment. These scores were consistent with the focus in FBT on parental management of eating disorder symptoms, as was the fact that alliance between adolescents and therapists was lower. Although parental therapeutic alliance was likely important in FBT, its role in treatment response remains uncertain.
Video streaming over MANETs: Testing and analysis using real-time emulation

In this paper, we design and deploy a Mobile Ad hoc Network (MANET) testbed that is integrated with EXata-Cyber network emulator to evaluate the performance of real-time video streaming applications. EXata-Cyber can unvaryingly connect emulated networks (virtual networks created by EXata-Cyber) to real machines. Thus, in our testbed, real machines can exchange real-life applications traffic over emulated wireless networks consisting of virtual machines. With the emulation capabilities of EXata-Cyber, our developed testbed gives an efficient, high fidelity and accommodating testing terrain for analyzing the performances and behaviors of real-life applications, machines and MANET routing protocols. We evaluate the performance of both proactive and reactive routing protocols while transmitting real-time video traffic in terms of change in network load, network mobility and video streaming bit rate. Furthermore, to provide accurate measures for perceived video quality at users end in the form of Quality-of-Experience (QoE), we evaluate and analyze metrics such as Mean Opinion Score (MOS), Signal-to-Interference and Noise Ratio (SINR) and Packet Delivery Ratio (PDR) at various layers of TCP/IP protocol stack.
Immunoregulating Properties of Peptides Related to Tumor Rejection Antigens: Effect on Human Monocytes and Natural Killer Cells

The authors analyzed the effect of several 15-amino acid peptides with sequences related to tumor-rejection antigens, tyrosinase, and the MAGE family on peripheral blood mononuclear cells from healthy donors cultured for periods of 1 to 7 days. Some of these peptides promoted stimulation of monocytes, manifested by phenotypic changes, release of interleukin (IL)-1a, IL-6, and tumor necrosis factor-&agr;, and induction of nitric oxide synthase on differentiated CD14++/+CD16+DR++ monocytes. An increase in the percentage of cytotoxic monocytes (CD14+/−CD16+) containing granule-associated DNase activity was also observed. Active peptides induced the release of IL-2 and interferon-&ggr;. Nonspecific natural killer and lymphokine-activated killer cell–mediated cytotoxicity was also observed against classical target cell lines (K-562 and Daudi) and allogenic melanoma cell lines AC and BB, together with an increase in granule-associated DNase in the natural killer cell–enriched population. Monocytes were needed to enhance this innate response, because peptides failed to induce the release of IL-2 on monocyte-depleted peripheral blood mononuclear cells. Data show an enhancement of the rapid innate immune response by peptides related to tumor rejection antigens and suggest that they could also determine the nature of a slow and more definitive specific immune response against tumor cells.
Di-μ-chlorido-bis[aqua(2,2′-bipyridine-κ2 N,N′)chloridocobalt(II)]

The title complex, [Co2Cl4(C10H8N2)2(H2O)2], is composed of two CoII atoms, each hexacoordinated by three Cl atoms, one 2,2′-bipyridine (bpy) ligand and one water molecule in a distorted octahedral geometry. Neighboring CoII atoms are linked together by two Cl bridges, forming a dinuclear CoII complex with inversion symmetry. There are intermolecular O—H⋯Cl hydrogen bonds and intermolecular π–π stacking interactions between adjacent bpy ligands [centroid–centroid distance = 3.617 (2) Å] in the structure.
Computing oxygen‐enhanced ventilation maps using correlation analysis

Correlation maps of oxygen‐enhanced ventilation were obtained in nine healthy volunteers using complete and selected image series. The complete series included all images acquired with the subjects alternately inhaling room air and 100% oxygen. The selected series were the subsets of the complete series and included only co‐registered images that showed matched diaphragmatic position at maximal expiration. Cross‐correlation was computed between the time response function of each pixel and the input function representing the alternation between periods of room air and 100% oxygen inhalation. The confidence level for the correlation analysis was set to 0.01. Pulmonary parenchymal anatomy was consistently reproduced throughout the lung, even in anterior slices where published data have reported correlation problems. The overall average correlation coefficient was 0.66 ± 0.07 for the complete series and 0.75 ± 0.08 for the selected series. It was concluded that correlation analysis could be used to reconstruct qualitative oxygen‐enhanced ventilation maps. Magn Reson Med 49:591–594, 2003. © 2003 Wiley‐Liss, Inc.
Towards the complete elimination of gate/switch level simulations

This paper presents the reasoning behind eliminating full-chip gate/switch-level simulations for microprocessors/digital system designs and utilizing RTL models for the purpose, provided formal boolean equivalence between RTL and gate/switch-level models have been established using symbolic simulation for all blocks that comprise the chip. No logic bug should go undetected if only RTL models are used for full chip simulations provided existing design methodologies are enhanced to incorporate a constraints checking flow coupled with a rigorous circuit metastability/contention prevention flow.
Transesophageal and transthoracic echocardiography and Doppler-examinations in systemic lupus erythematosus.

OBJECTIVE To search for cardiac abnormalities in systemic lupus erythematosus (SLE). METHODS 35 patients examined by 2-D transthoracal Doppler and transesophageal echocardiography. RESULTS Mitral and aortic valve abnormalities were seen in 12 patients (34%) respectively, and occurred altogether in 16 patients (46%). They were in general significantly associated with longer disease duration, but not with anticardiolipin antibodies (aCL), disease activity, or any other variable, except for time on corticosteroids. which was significantly longer in patients with aortic valve calcifications. CONCLUSION Valve masses and valve thickening--often in combination--are the most frequent structural findings in SLE, occurring more often on the aortic than on the mitral valves. Factors other than antiphospholipid antibodies, medication, hypertension, or coronary heart disease seem to be responsible for this phenomenon. Drugs that modulate inflammation in endo- and pericardial tissue may, at least in part, be responsible for the observed mitral valve calcifications and pericardial fibrosis.