Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of Uterine Biophysical Profile and to Assess its Role in Predicting Conception among Unexplained Primary Infertility Patients

Introduction: Infertility is a devastating disease which affects its victims at a very basic level the ability to reproduce. This can be divisive to the couples involved, their relatives and friends. The influence of infertility can be immense. There are a lot of medical and social consequences of infertility and the psychological sequelae are one of them. Affected patients and their families suffer from loss of esteem, disappointment and depression. Considering the immense effect of infertility on the life of not only the affected couples but also on their families and relatives the present study was conducted with following objective. Objective: To evaluate the Uterine Biophysical Profile and to assess its role in predicting the conception outcome in spontaneous cycles in patients with unexplained primary infertility. Material &Methods: A prospective observational study was conducted in the Department of Obstetrics and Gynaecology, U.P. Rural Institute of Medical Sciences & Research, Saifaion 55 women with unexplained primary infertility after standard diagnostic work up. Ultrasound (TVS) measurement of all patients was performed in their midcycle of spontaneous cycle. The Uterine Biophysical Profile (UBP) i.e. certain sonographic qualities of the uterus were noted during the normal mid-cycle of these patients. These included 7 parameters: Endometrial thickness in greatest AP dimension of 7 mm or greater (full-thickness measurement), a layered ("5 line") appearance to the endometrium, myometrial contractions causing a wave like motion of the endometrium, homogeneous myometrial echogenicity, uterine artery blood flow (as measured by PI, less than 3.0), blood flow within zone 3 using color doppler technique, myometrial blood flow seen on gray-scale examination. The Uterine Scoring System for Reproduction ("USSR") was used to evaluate the total score. Results: Among 55 unexplained primary infertility patients 24 i.e. 43.63% conceived by serial ultrasonographic monitoring of spontaneous menstrual cycle and timed intercourse. According to USSR, with a ‘perfect score’ of 20, there was 80% conception rate. While 9 /15 patients (i.e 60%) conceived with a score of 17-19. With a score of 14-16, 10/23 patients conceived i.e. 43.37%. Only 8.33% conception rate was seen with a low score of < or = 13. Highest pregnancy rate (60%) was seen with an endometrial thickness of 7-9mm while zone IV endometrial blood flow gave maximum conception rate of 66.66%. Conclusion: UBP can prove to be a simple, reliable, reproducible, rapid and non-invasive tool to predict uterine environment and hence conception outcome.
Identificación de nuevos factores pronósticos clínicos e inmunogenéticos en el adenocarcinoma renal

El carcinoma renal (CR) constituye el 2,6% de todas las neoplasias malignas primarias del adulto. Es la causa del 3% de las muertes por cancer. La mayor incidencia se produce a partir de los 40 anos. La variedad histologica de celulas claras del CR constituye el 85% de las neoplasias malignas primarias del rinon. La incidencia del CR ha aumentado progresivamente en las ultimas cuatro decadas en Espana y en el resto del mundo occidental, a razon de un 3% anual. Varios factores de riesgo tienen demostrada su influencia en el desarrollo del carcinoma renal, como el tabaco, obesidad, hipertension, insuficiencia renal cronica y dialisis, factores ocupacionales, habitos alimenticios y el riesgo genetico en el caso del carcinoma renal hereditario.
The Positional Effect in Soft Classification Accuracy Assessment

Recent research has included the rapid development of soft classification algorithms and soft classification accuracy assessment beyond the traditional hard approaches. However, less consideration has been given to whether conditions and assumptions generated for the hard classification accuracy assessment are appropriate for the soft one. Positional error is one of the most significant uncertainties that need to be considered. This research examined the impacts of positional errors on the accuracy measures derived from the soft error matrix using NLCD 2011 as reference data and several coarser maps generated from NLCD 2011 as classification maps at the spatial resolutions of 150m, 300m, 600m, and 900m. Eight study sites, with a spatial extent of 180km×180km, of different landscape characteristics were investigated using a two-level classification scheme. Results showed that with existing registration accuracies achieved by current global land cover mapping, the errors in overall accuracy (OA-error) were 2.13% -39.98% and 2.53%-48.82% for the 8 and 15 classes, respectively and the errors in Kappa (Kappa-error) were 6.64%-57.09% and 7.08%-58.81% for the 8 and 15 classes, respectively if soft classifications were implemented based on images where spatial resolutions varied from 150m to 900m. More complex landscape characteristics and classes in the classification scheme produced a greater impact of the positional error on the accuracy measures. To keep both OA-error and Kappa-error under 10 percent, the average required registration accuracy should achieve 0.1 pixels. This paper strongly recommends the addition of uncertainty analysis due to positional error in future global land cover mapping.
Can You, and Should You, Buy an Innovation Hub?

This paper offers some of the first empirical analysis on the impact of innovation hubs on firm and local performance. The Silicon Valley innovation hub is frequently cited as evidence for the success innovation hubs bring through spillover effects which boost local economies. I exploit Microsoft’s 1979 relocation from Albuquerque, New Mexico, to Bellevue, Washington, to analyze the effect of the Seattle innovation hub on its local economy. Using a difference-in-difference approach with quasi-synthetic controls, I find three main results. First, there is no strong evidence for Microsoft triggering the development of a Seattle innovation hub. Second, to the extent to which the Seattle Hub exists, it does not perform significantly better when looking at firm and local performance. Finally, there is evidence that innovation hubs incur higher rent that potentially constrains growth. ∗vickyyeung@stanford.edu Sincere thank you to Nicholas Bloom, whose guidance has helped me grow into a more critical yet thoughtful researcher. I would like to thank Enrico Moretti for his insight in the preliminary analysis and Marcelo Clerici-Arias for his dedication to the honors program. This research has benefited from helpful comments from Scott Cunningham, Marcel Fafchamps, Mikidadu Mohammed; and conference, seminar, and research symposia audiences at the Federal Reserve Bank of Dallas and Stanford University. A huge thank you to Robert Fletcher for his unwavering support and encouragement throughout. I thank Woods & Poole Economics Inc. for generously providing GDP data.
Massively Parallel Computation of Skyline Queries with FPGAs

Due to stagnant clock speeds and high power consumption of commodity microprocessors, database vendors have started to explore massively parallel co-processors such as FPGAs to further increase performance of their systems. A typical approach is to push simple but compute-intensive operations (e.g., compression/decompression, filtering based on projection and/or selection, etc.) to FPGAs for accelerated processing. In this paper, we show how a significantly more complex operation—the computation of the skyline—can be holistically implemented on an FPGA. A skyline query computes the pareto optimal set of multi-dimensional data points stored in a database. These queries are very compute-intensive and have been studied in software extensively over the last decade. However, our work is the first to examine skyline computation on FPGAs. To solve skyline queries in hardware, we propose a methodology that interleaves data storage and computation, allowing multiple operations to be executed on the same working set in parallel, while accounting for all data dependencies. Our experiments show that we achieve very promising results compared to CPU-based solutions. Keywords-FPGA, database, pareto optimal, skyline query
Use and perceived ease of obtain ing illicit drugs among teenagers in urban, suburban and rural schools: A UK study

In March 1995 a survey of alcohol, tobacco and illegal drug use was carried out on 7722 teenagers born in 1979 who were attending a sample of 69 state and private schools throughout the United Kingdom. The sample was divided according to the urban, suburban or rural location of the schools, and the use of various psychoactive substances was studied according to this classification. Use of cannabis (marihuana) within the past 30 days and lifetime use of MDMA (ecstasy) were both significantly less common in the rural schools. Access to ecstasy was also seen as more difficult by teenagers in the rural schools. However, these differences were not large and no other significant differences were found. In general, use of illegal substances by 15–16 year olds did not appear to be much different in rural, suburban and urban areas. These findings confirm the increasingly widespread nature of drug use among British youth.
Shifter Lists—A Data Structure for Massive Parallelism

A wide range of technology trends are creating the opportunity to use highly parallel co-processors next to conventional CPUs to improve the performance of data processing systems. However, it is often difficult to exploit the inherent parallelism in these devices. Most systems available focus on ad-hoc implementations of single operators. Rather than focusing on how to parallelize a given operator, in this paper, we propose a new data structure—shifter lists—that has been designed to support data processing on massively parallel hardware (hundreds to thousands of processing elements). A shifter list can accommodate processing of arbitrary complexity at each processing stage while guaranteeing throughput-optimized processing. In the paper we present shifter lists, characterize their behavior, show a first implementation (on an FPGA, for generality), and apply the result to a use case (skyline queries) to show how to determine when this type of solution makes practical sense.
The Stylish Autoencoder

Textual style transfer is a developing area of research. The majority of works on the task try to disentangle the content and the style in the text using generative models and adversarial losses. In this work we propose a new method for training an attentive stylish text generation model without disentanglement using back tracking. Our model is easy to train and computationally efficient. It is a self-attention-based encoder decoder, trained with the supervision of pretrained style classifier.
Equity in utilization of health care services in Turkey: an index based analysis.

Background Equity in the use of health care services is an issue which has increasingly been on the health policy agenda over recent years in both middle- and low-income countries. Aims The purpose of this study was to investigate the degree and progress of equity in health care utilization in Turkey during 2008-2012. Methods Wed use data from health surveys (2008, 2010, 2012) conducted by the Turkish Statistical Institute. The concentration index (CI) and the horizontal equity index (HI) were calculated as a measure of equity, and a Blinder-Oaxaca decomposition analysis was applied. Results The general practitioner (GP), specialist and inpatient visits display a pro-poor orientation. Averages of the CI and HI indices for 2008-2012 were 0.74 and -0.17 for GP visits, 0.75 and -0.13 for specialist visits, 0.83 and -0.31 for inpatient visits. Conclusion Our findings indicate that health care utilization in Turkey appears to have become equitable over the years; however, the sustainability of equity is an issue of concern.
Using National Student Survey (NSS) qualitative data and social identity theory to explore students’ experiences of assessment and feedback

ABSTRACT Assessment and feedback are interrelated challenges for higher education, being perceived as key facets of the quality assurance of degrees, and yet commonly found to be sources of dissatisfaction for students. We performed a thematic analysis on the free-text comments of the National Student Survey for a large, Scottish, Russell Group university and found recurring themes of alienation versus belonging in how the students discussed assessment. We used Social Identity Theory to explore these themes and concluded that assessment can act as a barrier between staff and students, especially where students are not given effective feedback. When students feel their assessment excludes them from a group (such as their discipline), they express dissatisfaction and frustration. This study adds to the growing body of work encouraging a dialogic approach to ensure students are able to make the best use of feedback and suggests it may also have the encouraging side-effect of improving student satisfaction.
UNIIATERAL FORCED NOSTRIL BREATHING: Basic Science, Clinical Trials, and Selected Advanced Techniques

This arricle reviews the published basic science and clinical studies on unilateral forced nostril breatbing (UFNB), a subset of yogic breathing (ptanayam) techniques that were discovered/devised more than 5000 years ago. The relationship of UFNB to the ultradian physiological phenomenon called the nasal cycle, a marker of mind-body states is also reviewed. Basic science studies show how UFNB can affect the autonomic nervous system, central nervous system (including cognition), and general metabolic activities. Clinical trials on the application to angina pectoris and obsessive compulsive disorder are described, In addition, three selected advanced UFNB techniques are described; one for stimulating the immune system; one for developing a comprehensive, comparative, and intuitive mind; and a third for developing an enlightened-transcendent mind. These three techniques are part of the ancient science of Kundalini Yoga as taught by Yogi Bhajan.
Parameter Identification in a Estimated New Keynesian Open Economy Model

In this paper, we use Monte Carlo methods to study the small sample properties of the classical maximum likelihood (ML) estimator in artificial samples generated by the NewKeynesian open economy DSGE model estimated by Adolfson et al. (2008) with Bayesian techniques. While asymptotic identification tests show that some of the parameters are weakly identified in the model and by the set of observable variables we consider, we document that ML is unbiased and has low MSE for many key parameters if a suitable set of observable variables are included in the estimation. These findings suggest that we can learn a lot about many of the parameters by confronting the model with data, and hence stand in sharp contrast to the conclusions drawn by Canova and Sala (2009) and Iskrev (2008). Encouraged by our results, we estimate the model using classical techniques on actual data, where we use a new simulation based approach to compute the uncertainty bands for the parameters. From a classical viewpoint, ML estimation leads to a significant improvement in fit relative to the log-likelihood computed with the Bayesian posterior median parameters, but at the expense of some the ML estimates being implausible from a microeconomic viewpoint. We interpret these results to imply that the model at hand suffers from a substantial degree of model misspecification. This interpretation is supported by the DSGE-VAR() analysis in Adolfson et al. (2008). Accordingly, we conclude that problems with model misspecification, and not primarily weak identification, is the main challenge ahead in developing quantitative macromodels for policy analysis.
THE IMPACT OF MONETARY POLICY SURPRISES

This paper examines the effect of monetary policy surprises on energy prices at intraday, daily, and monthly frequencies. We measure monetary policy shocks using changes in interest rate futures prices that capture unexpected changes in the fed funds target rate.We find a significant response of energy prices to surprise changes in the fed funds target rate in an intraday window immediately following the monetary announcement. However, the accumulated responses of energy prices to monetary shocks over a period of several days after the announcement are statistically insignificant. We also use fed funds futures data to identify the contemporaneous impact of monetary policy shocks on oil prices in a monthly structural vector autoregressive (VAR) setup. We find no statistically significant effect of federal funds rate shocks on oil prices. The VAR estimates support the assumption of no contemporaneous feedback from monetary policy to energy prices. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark 35:87–103, 2015
Shifter Lists—Interleaving Data Storage and Computation

Database system vendors have started to explore massively parallel co-processors such as FPGAs to further increase performance of their systems. However, the lack of suitable abstractions often makes it difficult to map a given database task to these devices and fully exploit their inherent parallelism. In this paper, we focus on one such abstraction that can be applied to a common class of compute-intensive database operators that are based on nested loops. We propose a new data structure—a shifter list—for FPGAs that interleaves data storage and computation, allowing multiple operations to be executed on the same data structure in parallel while implicitly avoiding race conditions and other potential conflicts. The shifter list abstraction allows many related database tasks, e.g., top-k queries, k-nearest neighbor search (k-NN), and skyline queries to be brought to FPGAs for improved performance. In this paper, we apply shifter lists to skyline queries, as one possible use case. Our experiments show that we achieve very promising results compared to CPU-based solutions.
The Factors that Influence on Firm Value and Company Performance as Mediation Variables (Study Manufacturing Companies period 2015-2017)

This study examined the influence of Leverage and Size on Firm Value that was measured by Price to Book Value and Company Performance that measured by Return on Assets as a mediating variable. The sample of this study used 60 manufacturing companies listed on Indonesian Stock Exchange period 2015-2017. This study was tested using Warp Partial Least Square program to prove the hypothesis proposed. The results showed that Leverage had no effect on Return on Assets and had a significant positive effect on Price to Book Value. Meanwhile Size had a significant positive effect on Return on Assets but it did not have a direct effect on Price to Book Value. Returrn on Assets had a positif and significant effect on Price to Book Value. Return on Assets did not act as a mediating variable in the relationship between Leverage and Price to Book Value, but in the Size and Price to Book Value relationship, the Return on Assets variable act as a mediating variable.
INTRODUCTION: MAKING A CASE FOR DISCOURSE ANALYSIS IN FOREIGN LANGUAGE TEACHER EDUCATION

The concept of heteroglossia is extremely interesting to me. I recently gave a paper in which I discussed Ingeborg Bachmann’s Malina and asserted that the main character had basically two voices: one masculine, one feminine. I found it fascinating after reading the chapter in Fowler [1996] to think about the possibility of not merely two, but perhaps multiple voices. The notion of voice has been a topic of particular importance in feminist criticism, because women have debated how to find a voice in which to write that is not merely a reproduction of the “master discourse”. Yet if we consider voice to be heteroglossic, then it makes little sense to think of a master discourse, which would be, by virtue of definition, singular. (Fran, reaction journal)
' s personal copy Macroeconomic cycles and the stock market ’ s reaction to monetary policy q

This paper examines cyclical variation in the effect of Fed policy on the stock market. We find a much stronger response of stock returns to unexpected changes in the federal funds target rate in recession and in tight credit market conditions. Using firm-level data, we also show that firms that face financial constraints are more affected by monetary shocks in tight credit conditions than the relatively unconstrained firms. Overall, the results are consistent with the credit channel of monetary policy transmission. 2008 Elsevier B.V. All rights reserved.
Evaluation of a survivorship care plan: long-term use, care coordination and quality of life in breast cancer survivors

SUMMARY Aim: This study evaluated the use and impact of a survivorship care plan (SCP) in breast cancer survivors. Methods: An SCP was implemented at the end of treatment in a cohort of 68 Australian breast cancer survivors. Utility, cancer care coordination, satisfaction with medical care, quality of life and unmet needs were measured at baseline, 6 and 18 months. Results: In total, 56% of participants at 6 months and 51% at 18 months reported continued use of the SCP during follow-up consultations. Younger women were more likely to use the SCP. Overall quality of life improved over time, however, endocrine symptoms worsened significantly, especially in younger women. Conclusion: Younger women, who frequently suffer from debilitating endocrine symptoms, may be the group most likely to benefit from an SCP.
An Analysis of Korean Bank Performance Using a Double Bootstrapped DEA Analysis

The purpose of this study is to analyze the efficiency of Korean banks using a two-stage DEA (data envelope analysis) bootstrap procedure suggested by Simar & Wilson (2007). The study comes approximately two decades after the Korean financial crisis which had a devastating impact on the Korean banking sector and economy. The crisis exposed the underpinnings of extremely liberal lending policies which prompted numerous banking reforms by the government. In the first stage of the two-stage DEA procedure, the relative efficiency scores of Korean banks are estimated. Then, in the second stage, the effect of certain environmental variables is estimated using a truncated regression model. The results of this paper suggest a continuing tension between Korean bank profitability and bank revenue.
Storage of hatching eggs in the production process

Due to dynamic market demands for day old chicks and the large scale of commercial hatcheries, the storage of hatching eggs is often unavoidable. Although the detrimental effects on hatchability and chick quality have been known for a long time, hatchery managers aim for an optimal utilisation of the considerable capacity of modern incubators and to minimise transports from farm to hatchery. In this way, efficiency is optimised and costs are reduced. Even though managers are aware of the measures that can be taken to reduce damage, we noticed that difficulties arise as regards the implementation of these measures in hatchery practice. However, losses due to prolonged egg storage can be greatly reduced by the consistent application of these methods in the planning schedules of hatcheries. Furthermore, results from recent studies reveal new aspects concerning the events that occur during storage.
A Residual Neural-Network Model to Predict Visual Cortex Measurements

Understanding how the visual cortex of the human brain really works is still an open problem for science today. A better understanding of natural intelligence could also benefit object-recognition algorithms based on convolutional neural networks. In this paper we demonstrate the asset of using a residual neural network of only 20 layers for this task. The advantage of this limited number is that earlier stages of the network can be more easily trained, which allows us to add more layers at the earlier stage. With this additional layer the prediction of the visual brain activity improves from 10.4% to 15.53%.