Miracle-dz/UniFAR-FTUs huggingface dataset:
Macroeconomic Gains from Structural Fiscal Policy Adjustments: The Case of Colombia

Policymakers worldwide are drawing key lessons from recent debates on the role of fiscal policy in the recovery of advanced economies. Interestingly, in the late 1990s, facing the collapse of their economies, many emerging market economies addressed some of the focal issues currently discussed, such as the timing of fiscal adjustments, the need of fiscal impulses and their scope, the effectiveness of fiscal instruments along the cycle and the thresholds above which public-debt would hamper economic growth. In this paper, we present some evidence from Colombia suggesting that fiscal consolidation may have important effects on the behavior of the macroeconomy. Using structural nonlinear impulse response functions, we find that a fiscal policy that reduces the structural fiscal deficit, decreases the Government currency mismatch and deepens the local fixed-rate public bond market results in stronger reactions of output to Government expenditure shocks and in greater responses of market interest rates to monetary policy shocks
Cloning , Expression and Purification of a novel anti-angiogenic factor-Tumstatin Research Article

Chongbi Li1,*, Liming Yang2, Hongli Jia3 The Center of Biopharmaceutical Research and Development of Zhaoqing University, 526061, China (PR) Institute of Microbiology, Chinese Academy of Sciences, Beijing 100080, China (PR) The Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing 100071, China (PR) __________________________________________________________________________________
Chapter 743 Superiority by a Margin Tests for Simple Linear Regression

The correlation coefficient is used when X and Y are from a bivariate normal distribution. That is, X is assumed to be a random variable whose distribution is normal. The values of X will not be known until the study is completed. In the simple linear regression context, no statement is made about the distribution of X. In fact, X does not have to be a random variable. In this procedure the distribution of Y is conditioned on X.
K-means Parallelism on FPGA

NORTHEASTERN UNIVERSITY Prof. Miriam Leeser Department of Electrical and Computer Engineering Master of Science by Kai Huang The K-means algorithm, which partitions observations into different clusters, is often used for extremely large dataset analysis in data mining. A big issue with K-means execution is the large amount of time required, especially when applied to large data sets. Software parallelization methods, such as OpenMP, MPI, CUDA or MPI-CUDA, can only achieve limited acceleration over the sequential code, because the execution paradigm of the K-means algorithm is better suited to hardware pipelining. In this research, the algorithm is mapped to Field Programmable Gate Array (FPGA) hardware using an RTL implementation that overlaps the assignment and update steps and achieves a throughput balance between these two steps. The implementations are developed on two platforms, Gidel and Amazon Web Services F1 instance, which both provide hardware infrastructure and software development toolkits. The results of this research show that a hardware implementation could achieve at least two orders of magnitude speed up and is scalable to extremely large data sets.
Reexamining CO 2 Storage Capacity and Utilization of the Utsira Formation Odd Andersen ∗ ( SINTEF )

In this work we provide estimates of CO2 storage capacity of the Utsira Formation using the recently provided datasets from the Norwegian Petroleum Directorate, taking CO2 density variation into account. We also investigate strategies on how to realize as much as possible of this potential in large-scale injection scenarios. We base our study on the assumption that the limiting factor for CO2 storage at Utsira is the efficient use of available trapping mechanisms, with pressure buildup being of secondary concern. We consider the trapping mechanisms considered most important for the medium-to-long term (structural, residual and dissolution trapping), using a combination of modeling tools based on the Matlab Reservoir Simulation Toolbox (MRST).
DEPENDENCE OF THE ESR SPECTRA INTESITY OF 2 : OPOBN ADDUCT ON THE CONCENTRATIONS COMPONENTS IN NON-FENTON REACTION

important and are widely studied because they play a crucial role in the life and defense processes of cells as well as they are responsible for pathology cases in medicine [2, 3]. In biological cells the most important sources of radicals is the transport of electrons for example in photosynthesis. The leakage of electrons from this chain causes the reduction of oxygen species. In vitro the hydroxyl radicals are created in the Fenton reaction [4, 5]. On the contrary, the peroxide radicals are products of the non-Fenton reaction [6, 7]. The living time of the wide group of free radicals is a short period ranged from a few nanoseconds up to a few minutes. The peroxide anion radical is a very short-lived oxidant specie and therefore, it can be investigated by ESR using the spin trapping method [7]. In this paper we present such measurements using POBN trap for different concentrations of components in the H2O2 / KOH / DMSO system. The aim of the studies was experimentally determination such relative concentration of the components at witch the intensity of ESR signal is the best.
A Lifetime Reliability-Constrained Runtime Mapping for Throughput Optimization in Many-Core Systems

Due to technology scaling, lifetime reliability is becoming one of the major design constraints in the performance optimization of future many-core systems. Given a lifetime reliability constraint, the existing lifetime-constrained runtime mapping schemes often lead to low throughput because of the requirement to map all applications to compact regions. In this paper, we propose a runtime application mapping scheme that exploits a borrowing strategy to improve the throughput of many-core systems given a lifetime constraint. First, we propose using different strategies for mapping communication-intensive applications and computation-intensive applications. The lifetime reliability constraint can be relaxed in the local time scale when the communication requirement is high. The throughput is improved because the communication distance of communication-intensive applications is optimized while the waiting time of computation-intensive application is reduced. Then, we propose a method to effectively classify applications depending on the communication-to-computation ratio. A dynamic threshold is determined according to the current locations of available cores. Finally, we propose an improved neighborhood allocation scheme to reduce the communication cost in the task mapping. The experimental results show that compared to the state-of-the-art lifetime-constrained mapping, the proposed mapping scheme improves the throughput of many-core systems by 26% on average for synthetic task graphs and by 20% on average for realistic task graphs while the lifetime reliability is maintained within a constraint.
AutomAtic Detection of morphologicAl pArADigms using corporA informAtion

This paper deals with automatic induction and prediction of morphological paradigms for Russian. We apply a method of longest common subsequence to extract abstract paradigms from inflectional tables. Then we experiment with the automatic detection of paradigms using a linear classifier with lexeme suffixes and prefixes as features. We show that Russian noun paradigms could be automatically detected with 77% accuracy per paradigm and 93% accuracy per word form, for Russian verbs per-paradigm accuracy reaches 76% and per-form accuracy is 89%. Usage of corpora information and character n-grams allows to improve these results up to 82% and 95% for nouns and 86% and 95% for verbs.
Old Age and Loneliness : Cross-sectional and Longitudinal Analyses in the Tampere Longitudinal Study on Aging

The purpose of this study was to examine whether older age is associated with increasing loneliness in people aged 60 and over. Data came from TamELSA, a population-based prospective longitudinal study in Tampere, Finland. The follow-up time was 20 years. Loneliness was measured by a single question – “Do you feel lonely? ” – with the possible answers often, sometimes, or never. Cross-sectional analysis showed that the percentage of subjects feeling lonely increased toward older age groups, but in a multivariate analysis, only household composition and social participation were independently associated with loneliness. Longitudinal analysis showed that loneliness increased with higher age. Over a 10-year period, loneliness increased most in those who, at baseline, were married and living alone with their spouse. In conclusion, only a minority of older people continuously suffer from loneliness. Loneliness does increase with age, not because of age per se, but because of increasing disability and decreasing social integration. Manuscript received: / manuscrit reçu : 12/09/02 Manuscript accepted: / manuscrit accepté : 29/11/03 Mots clés : vieillissement, suivi, études longitudinales, solitude, vieillissement, bien-être
The relationship between oil and agricultural commodity prices in south africa: a quantile causality approach

ABSTRACT:The increase in agricultural commodity prices in the recent past has renewed interest in ascertaining the factors that drive agricultural commodity prices. Though a number of factors are possible, higher oil prices are thought to be the major factor driving up agricultural commodity prices, especially as the demand for biofuels production increases. However, empirical evidence of this relationship remain ambiguous and largely depends on the method used. For this reason, there is a need to examine the relationship in the context of different methodologies. Furthermore, information on how South African commodity prices respond to world oil price shocks is less certain. A good understanding of the factors that drive local commodity prices will assist in making sound agricultural policies. In this paper, the Granger causality test is applied to the mean to investigate the causality between oil prices and agricultural (soya beans, wheat, sunflower and corn) commodity prices in South Africa. Daily data spanning from 19 April 2005 to 31 July 2014 is used for Brent crude oil, corn, wheat, sunflower and soya beans prices. Agricultural commodity prices were obtained from the Johannesburg Stock Exchange, and the series of Brent crude oil prices from the U.S. Department of Energy. Results from the linear causality test indicate that oil prices do not influence agricultural commodity prices. However, owing to structural breaks and nonlinear dependence between the variables of study, these results are misleading. As an alternative, the nonparametric test of Granger causality in quantiles, as proposed by Jeong, Härdle and Song (2012) is used. Through this test, we not only look at causality beyond the mean estimates but also accounts for the structural breaks and nonlinear dependence present in the data. Additionally, the method becomes more instructive in the case where the distribution of variables has fat tails. The findings show that the effect of changes in oil prices on agricultural commodity prices vary across the different quantiles of the conditional distribution. The highest impact is not at the median, and the impact on the tails is lower compared to the rest of the distribution. The analysis shows that the relationship between oil prices and agricultural commodity prices depends on specific phases of the market, and therefore contradicts the neutrality hypothesis that oil prices do not cause agricultural commodity prices in South Africa. This implies that policies to stabilize domestic agricultural commodity prices must consider developments in the world oil markets.
Development of Quantitative Structure-Activity Relationships ( QSARs ) and Their Use for Priority Setting in the Testing Strategy of Endocrine Disruptors

Considerable scientific, regulatory and popular press attention has been devoted to the Endocrine Disrupting Chemicals (EDCs), of which estrogenic chemicals figure prominently. A large number of potential estrogenic EDCs are associated with products regulated by the Food and Drug Administration (FDA), including plastics used in food packaging, phytoestrogens, food additives, pharmaceuticals, cosmetics, etc. Recent legislation mandates the U.S. Environmental Protection Agency (EPA), a sister regulatory agency, to develop a screening and testing program for potential EDCs in drinking water and food additives. Under the legislation, a large number of chemicals will undergo various in vitro and in vivo assays for their potential estrogenicity, as well as other hormonal activities. There is a crucial need to set priority for these chemicals to reduce the cost and speed the screening and testing process. At the FDA National Center for Toxicological Research (NCTR), quantitative structure-activity relationships (QSARs) is a major component of the Endocrine Disruptor Knowledge Base (EDKB) project – a prototype Toxicological Knowledge Base. By integrating experimentation and modeling, a series of QSAR models have been developed and validated in the project. These models are integrated into a "Four-Phase" scheme, with each successive phase eliminating unlikely estrogen receptor (ER) binders, resulting in a priority listing of chemicals for regulatory application. The system performance has been validated using several data sets with known e strogenic activity and, subsequently, applied to three environmental data sets, identified by the EPA. It has also been used to assess estrogenic activity of chemicals of concern at other Centers within the FDA, namely the Center for Food Safety and Applied Nutrition (CFSAN) and the Center for Drug Evaluation and Research (CDER). The rigorous validation of the integrated system is ongoing via the interagency agreement (IAG) between EPA and NCTR. The approach presented here for estrogen is anticipated to be equally applicable for other receptor-mediated, endocrine disrupting mechanisms, e.g., androgen receptor binding, and other toxicity endpoints. REGULATORY RESEARCH PERSPECTIVES
Removal of an over-the-scope clip using the over-the-scope clip-removal system before performing polypectomy of the recurrent polyp

We present the case of a 64-year-old woman with no significant past medical history who was found during a screening colonoscopy to have a 45-mm sessile polyp at the hepatic angle. The initial resection attempt was complicated by massive spurting bleeding, which was controlled by adrenaline injection and the application of eight hemoclips. During the next colonoscopy, we observed adenomatous tissue with significant fibrosis and decided to perform endoscopic full-thickness resection (EFTR) with a “close and cut” technique using a 14/6 t over-the-scope (OTS) clip (Ovesco Endoscopy AG, Tübingen, Germany) [1, 2]. This resection was performed without any complications and the patient was discharged after 24 hours. At follow-up colonoscopy, performed after 6 months, we observed adenomatous tissue with low grade dysplasia that was confirmed histologically growing around the clip (▶Fig. 1). Therefore, we decided to remove the OTS clip and make a new attempt to resect the adenoma. We used a specific OTS clip-removal system (remOVE; Ovesco Endoscopy AG) to cut the clip [3, 4]; however, because of tissue overgrowing across the thinner area of the OTS clip, it was necessary to cut it into four pieces (▶Fig. 2; ▶Video 1). We then excluded perforation or any other complication and performed a piecemeal resection, achieving resection by electrocoagulation with the tip of a snare. The patient was discharged after a couple of hours of observation. The histology of the sample showed chronic inflammatory changes without adenomatous tissue. The OTS clip-removal system is a safe technique for removing OTS clips and can be combined with a new attempt at endoscopic mucosal resection without complications. Endoscopy_UCTN_Code_TTT_1AQ_2AD
TGFβ/BMP Signaling Pathway in Cartilage Homeostasis

Cartilage homeostasis is governed by articular chondrocytes via their ability to modulate extracellular matrix production and degradation. In turn, chondrocyte activity is regulated by growth factors such as those of the transforming growth factor β (TGFβ) family. Members of this family include the TGFβs, bone morphogenetic proteins (BMPs), and growth and differentiation factors (GDFs). Signaling by this protein family uniquely activates SMAD-dependent signaling and transcription but also activates SMAD-independent signaling via MAPKs such as ERK and TAK1. This review will address the pivotal role of the TGFβ family in cartilage biology by listing several TGFβ family members and describing their signaling and importance for cartilage maintenance. In addition, it is discussed how (pathological) processes such as aging, mechanical stress, and inflammation contribute to altered TGFβ family signaling, leading to disturbed cartilage metabolism and disease.
Factors, assessments and interventions related to job matching in the vocational rehabilitation of persons with spinal cord injury.

BACKGROUNDMatching an individual's capabilities, interests and needs with corresponding job demands and characteristics is an established procedure in vocational rehabilitation (VR). Yet, a systematic exposition of specific factors affecting the determination and attainment of a person-job match in VR practice is currently missing.OBJECTIVETo examine factors, assessments and interventions related to job matching (JM) in VR of persons with spinal cord injury (SCI) by using a literature-based conceptual JM framework.METHODSApplying a qualitative descriptive design, data were collected by overt non-participant observations across the VR process of two individuals with SCI, representing major return-to-work scenarios (returning to the pre-injury job and preparing for vocational retraining). RESULTSPerson-related, job-related and environmental factors were identified that either played a direct or indirect role in determining and attaining a person-job match. The factors were evaluated by different work-related and medical assessments and were targeted by a number of JM-related interventions.CONCLUSIONSWhile our conceptual framework may serve as a generic blueprint to facilitate JM approaches in VR practice, the specific factors identified in our study are particularly valuable for developing JM applications aimed at promoting sustainable return to work for persons with SCI.
Sensitive Deep Ultraviolet Photodetector and Image Sensor Composed of Inorganic Lead-Free Cs3Cu2I5 Perovskite with Wide Bandgap.

In recent years, solution-processable perovskite photodetectors have attracted increasing research interest due to their low-cost, ease of fabrication, and excellent optoelectronic properties. In this work, we reported a sensitive deep ultraviolet (DUV) light photodetector based on inorganic and lead-free Cs3Cu2I5 crystalline film derived by a solution method. Optoelectronic analysis revealed that the Cs3Cu2I5 device showed nearly no sensitivity to visible illumination with wavelength of 405 nm, but exhibited pronounced sensitivity to both DUV and UV light illumination with response speed of 26.2/49.9 ms for rise/fall time. The Ilight/Idark ratio was as high as 127. What is more, the responsivity and specific detectivity were as estimated to be 64.9 mA W-1 and 6.9×1011 Jones, respectively. In addition, the device could almost retain its photoresponse characteristics after storage in air environment for a month. It is also found that the capability of Cs3Cu2I5 crystalline film device can readily record still DUV image with acceptable resolution. The above results confirm that the present Cs3Cu2I5 crystalline film DUV photodetector may hold great potential for future DUV optoelectronic devise and systems.
Hybrid IRBM-BPNN Approach for Error Parameter Estimation of SINS on Aircraft

To realize the error parameter estimation of strap-down inertial navigation system (SINS) and improve the navigation accuracy for aircraft, a hybrid improved restricted Boltzmann machine BP neural network (IRBM-BPNN) approach, which combines restricted Boltzmann machine (RBM) and BP neural network (BPNN), is proposed to forecast the inertial measurement unit (IMU) instrument errors and initial alignment errors of SINS. Firstly, the error generation mechanism of SINS is analyzed, and initial alignment error model and IMU instrument error model are established. Secondly, an unsupervised RBM method is introduced to initialize BPNN to improve the forecast performance of the neural network. The RBM-BPNN model is constructed through the information fusion of SINS/GPS/CNS integrated navigation system by using the sum of position deviation, the sum of velocity deviation and the sum of attitude deviation as the inputs and by using the error parameters of SINS as the outputs. The RBM-BPNN structure is improved to enhance its forecast accuracy, and the pulse signal is increased as the input of the neural network. Finally, we conduct simulation experiments to forecast and compensate the error parameters of the proposed IRBM-BPNN method. Simulation results show that the artificial neural network method is feasible and effective in forecasting SINS error parameters, and the forecast accuracy of SINS error parameters can be effectively improved by combining RBM and BPNN methods and improving the neural network structure. The proposed IRBM-BPNN method has the optimal forecast accuracy of SINS error parameters and navigation accuracy of aircraft compared with the radial basis function neural network method and BPNN method.
Clinical performance of the HPV DNA Array genotyping assay in detection of CIN2+ lesions with BS GP5+/6+ MPG Luminex tested cervical samples

Human papillomavirus (HPV) detection is used for screening of cervical cancer and genotype‐specific persistence has shown to be mandatory for dysplasia development. Aim of this study was to evaluate the clinical performance of HPV DNA Array for cervical intraepithelial neoplasia 2+ (CIN2+) lesion detection. HPV DNA Array is a polymerase chain reaction‐based assay that targets E1 sequences of 29 HPV types (6, 11, 16, 18, 26, 31, 33, 35, 39, 40, 42, 44, 45, 51, 52, 53, 54, 56, 58, 59, 66, 67, 68, 69, 70, 73, 82, 85, and 97). The clinical evaluation was performed against the reference assay, BS‐GP5+/6+ multiplex genotyping (MPG)‐Luminex, with 600 cervical smear samples of a referral population. HPV DNA Array detected CIN2+ lesions with a sensitivity of 90.2%, identical to that of MPG‐Luminex. Detection of CIN3+ lesions was with a sensitivity of 90.3%, as compared with 88.7% of MPG‐Luminex. It demonstrated very good agreement for HPV detection, irrespective of type, of 91.5% (κ = 0.832). HPV DNA Array is a simple and robust assay, with a short protocol of 4 hours hands‐on time and automated readout by ELISpot AiDot software. It permits testing of up to 96 samples in one run and may be considered for use in organized screening programs and low resource settings.