Miracle-dz/UniFAR-FTUs huggingface dataset:
Standardized nomenclature, symbols, and units for bone histomorphometry: A 2012 update of the report of the ASBMR Histomorphometry Nomenclature Committee

Before publication of the original version of this report in 1987, practitioners of bone histomorphometry communicated with each other in a variety of arcane languages, which in general were unintelligible to those outside the field. The need for standardization of nomenclature had been recognized for many years,(1) during which there had been much talk but no action. To satisfy this need, B Lawrence Riggs (ASBMR President, 1985 to 1986) asked A Michael Parfitt to convene an ASBMR committee to develop a new and unified system of terminology, suitable for adoption by the Journal of Bone and Mineral Research (JBMR) as part of its Instructions to Authors. The resulting recommendations were published in 1987(2) and were quickly adopted not only by JBMR but also by all respected journals in the bone field. The recommendations improved markedly the ability of histomorphometrists to communicate with each other and with nonhistomorphometrists, leading to a broader understanding and appreciation of histomorphometric data. In 2012, 25 years after the development of the standardized nomenclature system, Thomas L Clemens (Editor in Chief of JBMR) felt that it was time to revise and update the recommendations. The original committee was reconvened by David W Dempster, who appointed one new member, Juliet E Compston. The original document was circulated to the committee members and was extensively revised according to their current recommendations. The key revisions include omission of terminology used before 1987, recommendations regarding the parameters and technical information that should be included in all histomorphometry articles, recommendations on how to handle dynamic parameters of bone formation in settings of low bone turnover, and updating of references.
Target detection for infrared polarization image in the background of desert

Infrared polarization imaging detection can be used to obtain not only the polarization state but also the radiation of target. With this method, the target that traditional photometry cannot detect can be settled. The degree and angle of polarization that used in polarization detection reflect different physical properties, and it is seriously redundancy along with intensity of images. A target detection method for polarization infrared image in the background of desert is proposed in allusion to the character. A modified kernel fuzzy clustering algorithm is purposed to cluster infrared images and the polarization images. Then to distinguish target from the background, the object information of clustered infrared and polarization image were combined according to sparse fusion method. Experimental results show that the proposed detection method is lower noise and more clearly details than wavelet fusion and laplacian pyramid fusion.
Sovereign Ratings and Oil-Producing Countries: Have Sovereign Ratings Run Ahead of Fundamentals?

We investigate whether rising oil prices have resulted in over-rating of oil-producing countries by rating agencies, after controlling for fundamentals. Based on a large dataset of countries from Standard and Poor's and Moody's, we find strong statistical evidence of a large ratings premium-nearly two notches-for those oil-producing countries with a large share of net oil revenue to gross domestic product, relative to countries with similar economic fundamentals. We have some limited forecast information from the rating agencies and the effect increases when we include this information, providing further evidence that this ratings premium is not driven by expected improvements in fundamentals. This finding has significant implications for asset prices in oil-producing countries and highlights the risk that in the event of a sharp unanticipated drop in oil prices, sovereign rating downgrades of oil-producing countries could be sharper than the deterioration in their economic fundamentals.
The Usefulness of Pension Obligation Estimates -Evidence from the Post-Financial Crisis Era

This paper examines whether, by requiring firms to base their discount rate assumption on current "high-quality" corporate bond yields, current pension standards produce less decision-useful estimates of pension obligations relative to the methodology used to calculate pension obligations under the Employee Retirement Income Security Act (ERISA). To assess decision-usefulness, I investigate how well alternative measures of firms' pension obligations reflect information used by investors and creditors relative to reported obligations (PBOGAAP). Using hand-collected data, I calculate alternative measures of firms' pension obligations using discount rates based on historical bond yields, similar to ERISA methodology. I find that PBOGAAP is a more credit relevant estimate of firms' pension obligations relative to all the alternative PBO estimates I calculate. However, I do not find a significant difference in the ability of PBOGAAP to explain equity prices relative to an alternative measure calculated using a discount rate assumption based on a 10-year historical average of bond yields. Using a pre-/post- financial crisis design, I provide weak evidence that this result could be consistent with investors doubting the usefulness of PBOGAAP in the post-financial crisis era due to the unique interest rate environment that existed during this time. The findings of this paper speak to the differences in the informational needs of investors and creditors. They may also inform standard setters about the usefulness of the pension obligation estimates produced by the current standards by investigating whether the usefulness of these estimates is affected by the interest rate environment in which they are calculated.
A study of inbreeding and kinship in intracranial aneurysms in the Saguenay Lac‐Saint‐Jean region (Quebec, Canada)

The genealogies of 533 individuals with an intracranial aneurysm (IA) born in the Saguenay‐Lac‐Saint‐Jean region, a geographically isolated area located in northeastern Quebec, were reconstructed using a population‐based register. A control group consisting of three individuals of the same sex and born on the same day and in the same municipality than the IA patients was created; the genealogies of the 1599 controls were also reconstructed. The coefficients of inbreeding and kinship were calculated. Familial aggregation, i.e. the presence of IA in two or more first‐ to third‐degree relatives, was also sought. The mean inbreeding coefficient was lower in the IA group than in the control group (7·92 × 10−4 versus 10·04 × 10−4). The mean kinship coefficient was higher in the IA group than in the control group (2·17 × 10−4 versus 1·55 × 10−4). Forty‐eight IA patients (9·0%) were first‐degree relatives compared to only 1·9% of the control individuals. The proportion of individuals showing familial aggregation was higher in the IA group than in the control group (29·8% and 18·6% respectively). These results strongly suggest that some IA are genetically determined in this population.
Plane Answers to Complex Questions: Theory of Linear Models

“look ahead” from the current observation to the next one, without actually processing it, by using multiple SET statements and the FIRSTOBS option. Unfortunately, the clinical study relegates the PROC FORMAT statements to the appendix. Because the author does not stress that this information is pertinent to the discussion, it might be overlooked. By altering the previous convention of putting everything needed within the chapter, the reader who unwittingly bypasses the appendix references could easily become confused. The ozone study introduces the INTCK function to simplify time and date processing and the MOD function to create group indexes. The library study uses the _TYPE_ variable to conveniently generate categories for PROC CHART and introduces the attractive tabular output format of PROC TABULATE. Chapter 12 “Useful Macros,” the crown jewel of the book, provides a summation of all of the functions, detailing their execution as compact macros code. It illustrates automatic differencing between successive observations and uses the %SYSFUNC and TRANWRD functions to automate variable pre xing and suf xing. I highly recommend this book to its target audience of SAS programmers and data analysts. It speaks to all levels of programming ability.
Low complexity resource allocation for OFDMA based on coalitional game theory

This work investigates a fair adaptive resource management criterion (in terms of transmit powers and subchannel assignment) for the uplink of an orthogonal frequency division multiple access (OFDMA) network, populated by mobile users with constraints in terms of target data rates. The inherent optimization problem is tackled with the analytical tools of coalitional game theory, and a practical algorithm based on Markov modeling is introduced. The proposed scheme allows the mobile devices to fulfill their rate demands exactly with a minimum utilization of network resources. Simulation results show that the average number of operations of the proposed iterative algorithm are much lower than K · N, where N and K are the number of allocated subcarriers and of mobile terminals.
Model Selection for Part of Speech Tagging With Type Supervision

Model selection (picking, for example, a parametric model family, a prior, and an estimation criterion) is crucial for building high-accuracy classifiers. In supervised learning settings, the accuracy of a model can be estimated on a labeled set and used to guide modeling decisions. In unsupervised or type-supervised learning settings, unsupervised model selection criteria are used, but their performance is far from optimal (Smith and Eisner, 2005). Here we propose a new model selection criterion for type-supervised sequence labeling settings, which uses the available weak supervision (type-level constraints) more directly to come up with an accuracylike metric. We evaluate the effectiveness of the method on type-supervised POS-tagging in nine languages, using both HMM and LDA-based models, and show that it outperforms two unsupervised model selection criteria.
A panel data analysis of FDI and informal labor markets

The objective of this paper is to examine whether informal labor markets affect the flows of Foreign Direct Investment (FDI), and also whether this effect is similar in developed and developing countries. With this aim, different public data sources, such as the World Bank (WB), and the United Nations Conference on Trade and Development (UNCTAD) are used, and panel econometric models are estimated for a sample of 65 countries over a 14 year period (1996-2009). In addition, this paper uses a dynamic model as an extension of the analysis to establish whether such an effect exists and what its indicators and significance may be. While the results shows that informal labor markets are significant and do positively affect the flow of FDI, these effects are felt up to a certain level of informality, above which the effect becomes negative. The results are similar for developed and developing countries and are robust to several checks.
Discussion of An Analysis of the Use of Accounting and Market Measures of Performance in Executive Compensation Contracts

This paper explores firms' use of accounting and market measures of performance in management compensation contracts. The authors argue that while market returns may be the "correct" measure of performance from the perspective of the shareholders, such measures may not be the best indicators of managerial actions. Relying on Holmstrom [1979], they argue that the important characteristic of a performance measure is whether it provides information on managerial action. In designing management compensation contracts, what matters is that the performance measure has a high signal-to-noise ratio, i.e., that the information about managerial action captured in the performance measure can be distinguished from the random noise in the measure. By imposing additional structure on the Holmstrom result, in the form of restrictions on the agents' utility functions and on the distribution of outcomes, the authors are able to convert the optimal compensation package into a linear function of stock returns and accounting returns. Additional restrictions on the agents' utility functions and on the form of the compensation contract allow the authors to specify a multiperiod compensation contract in which the change in management compensation between any two periods is a function only of the "surprise" in market and accounting returns. The authors then estimate this model using time-series data on management compensation and market and accounting returns. According to the theory laid out in the paper, the ratio of the two coefficients in this regression represents the ratio of signal-to-noise ratios for market returns and accounting returns in the
Perceived ambiguity about cancer prevention recommendations: associations with cancer‐related perceptions and behaviours in a US population survey

Background Health information reaching the public today is often characterized by what decision theorists have termed ‘ambiguity’– i.e. uncertainty regarding the information’s reliability, credibility or adequacy. This is a critical problem, as growing research suggests that ambiguity has important effects–promoting pessimistic judgments about risks and potential outcomes of risk‐reducing behaviours, and lowering adoption of these behaviours. However, little is known about the public’s perceptions of ambiguity in the health information domain, the effects of these perceptions, and the factors that influence these effects.
Health Care Communication Issues in Multiple Sclerosis: An Interpretive Description

Communication between persons with chronic illness and their professional health care providers is a critical element of appropriate health care. As the field of health care communication evolves, it becomes apparent that aspects of the illness experience shared by those affected by specific diseases might be a source of particular insight into what constitutes effective or appropriate communications. This interpretive description of health care communication issues in multiple sclerosis was based on qualitative secondary analysis of a set of in-depth interviews and focus groups conducted with 12 persons with longstanding MS experience. Analysis of their accounts illustrates an intricate interplay between common features within the disease trajectory and the communications that are perceived as helpful or unhelpful to living well with this chronic illness. From the analysis of these findings, the authors draw interpretations regarding what might be considered communication competencies for those who care for patients with this disease.
Motion compensation for 3D tomographic reconstruction of stent in X-ray cardiac rotational angiography

This paper presents a novel method for 3D tomographic reconstruction of stent in X-ray cardiac rotational angiography. The method relies on 2D motion compensation of the projected image from two radiopaque markerballs located on each side of the stent. The two markerballs are on a guidewire, which is introduced in the artery. Under the assumption that the guidewire and the stent have the same motion during rotational acquisition, we propose an algorithm to correct locally cardiac stent motion on the 2D X-ray projection images. After correction, the 3D image of the deployed stent is reconstructed using the classical Feldkamp algorithm. Although the correction is an approximation, results on realistic simulated sequences demonstrate the efficiency of the method
WiSH: WiFi-based real-time human detection

Sensorless sensing using wireless signals has been rapidly conceptualized and developed recently. Among numerous applications of WiFi-based sensing, human presence detection acts as a primary and fundamental function to boost applications in practice. Many complicated approaches have been proposed to achieve high detection accuracy, but they frequently omit various practical constraints such as real-time capability, computation efficiency, sampling rates, deployment efforts, etc. A practical detection system that works in realworld applications is lacking. In this paper, we design and implement WiSH, a real-time system for contactless human detection that is applicable for whole-day usage. WiSH employs lightweight yet effective methods and thus enables detection under practical conditions even on resource-limited devices with low signal sampling rates. We deploy WiSH on commodity desktops and customized tiny nodes in different everyday scenarios. The experimental results demonstrate the superior performance of WiSH, which has a detection accuracy of >98% using a sampling rate of 20 Hz with an average detection delay of merely 1.5 s. Thus, we believe WiSH is a promising system for real-world deployment.
Tax Avoidance, Welfare Transfers, and Asset Prices

Does tax avoidance have any implications for financial markets? This paper quantifies the general equilibrium implications of tax avoidance by setting up an incomplete markets production economy model in which households pay capital gains taxes and have access to tax avoidance technologies provided by financial institutions. I find that changes in the level of tax avoidance have disproportionate effects on different groups of agents and generally benefit the old, wealthy and high income households and detrimental for young, poor and low income households. Furthermore, these changes have asset pricing implications primarily due to the distortion in the optimal portfolio allocation generated by capital gains taxation.
Effects of Dietary Calorie Restriction or Exercise on the PI3K and Ras Signaling Pathways in the Skin of Mice*

Weight control by exercise and dietary calorie restriction (DCR) has been associated with reduced cancer risk, but the underlying mechanisms are not well understood. This study was designed to compare the effects of weight loss by increasing physical activity or decreasing calorie intake on tumor promoter-induced Ras-MAPK and PI3K-Akt pathways. SENCAR mice were randomly assigned to one of the following five groups: ad libitum-fed sedentary control, ad libitum-fed exercise (AL+Exe), exercise but pair-fed at the amount as controls (PF+Exe), 20% DCR, and 20% DCR plus exercise (DCR+Exe). After 10 weeks, body weight and body fat significantly decreased in the groups of DCR, DCR+Exe, and PF+Exe when compared with the controls. AL+Exe did not induce weight loss due to, at least in part, increased food intake. Plasma IGF-1 levels reduced significantly in DCR and DCR+Exe but not PF+Exe. The protein H-Ras and activated Ras-GTP significantly decreased in TPA-induced skin tissues of DCR-fed mice but not exercised mice. PI3K protein, phosphoserine Akt, and p42/p44-MAPK were reduced, however, in both DCR and PF+Exe groups. Immunohistochemistry demonstrated that the significantly reduced H-Ras occurred in subcutaneous fat cells, while the reduced PI3K and PCNA took place only in the epidermis. Plasma leptin decreased in PF+Exe, DCR, and DCR+Exe, while the caspase-3 activity increased in DCR+Exe only. Genomic microarray analysis further indicated that the expression of 34 genes relevant to PI3K and 31 genes to the MAPK pathway were significantly regulated by either DCR or PF+Exe treatments. The reduced PI3K in PF+Exe mice was partially reversed by IGF-1 treatment. The overall results of this study demonstrated that DCR abrogated both Ras and PI3K signaling, which might inhibit TPA-induced proliferation and anti-apoptosis. Selective inhibition of PI3K by PF+Exe but not AL+Exe seems more attributable to the magnitude of the caloric deficit and/or body fat loss than diet versus exercise comparison.
Application of Time-of-Flight Secondary Ion Mass Spectrometry to Automobile Paint Analysis

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) provides a method of elemental analysis that can distinguish among automotive paint samples of the same or nearly the same color. TOF-SIMS survey spectra were employed to determine the relative abundances of elements in the surface layers of the paint chips. The depth profile of paint samples permitted the analysis of small paint chips, the reproducible results for specific elements, and the identification of each car paint. Seventy-three samples of blue, red, white, and silver automobile paints from the major manufacturers in Korea were investigated using high resolution TOF-SIMS technique. It was found that paints of the same color produced by different manufacturers could be distinguished by this technique. TOF-SIMS is a reliable, nondestructive, and small area analyzing method for characterization of the elemental composition of automotive paint chips.
Data Mining of Dengue Infection Using Decision Tree

Dengue infection is an epidemic disease typically found in tropical region. Nowadays, the experts need to know the set of features on dengue infection in order to correctly classify the patients since these classes require different treatment. Our temporal dataset consists of clinical data and laboratory data. The data was collected from the first visit of patient until the date of discharge. We obtained 2 sources of datasets from different regions of Thailand which are Srinagarindra Hospital and Songklanagarind Hospital. Each dataset consists of more than 400 attributes. To accomplish the knowledge discovery task, we consider to employ decision tree as a data mining tool. We propose a set of meaningful attributes from the temporal data. Our experiments are divided into 4 parts. The first two experimental results show the useful knowledge to classify dengue infection from Srinagarindra Hospital’s dataset and Songklanagarind Hospital’s dataset, respectively. Each set of knowledge is tested by different dataset to make sure that the test data was a real unseen data. The third experimental results show the useful knowledge when we integrated 2 datasets. Another objective of this research is to detect the day of defervescence of fever which is called day0. The day0 date is the critical date of dengue patients that some patients face the fatal condition. Therefore the physicians need to predict day0 in order to treat the patients. They expect to have an intelligent system that can trigger the day0 date of each patient. Key-Words: Data Mining, Dengue infection, the day of defervescence.