Miracle-dz/UniFAR-FTUs huggingface dataset:
ANÁLISE SIMBÓLICA DE INTERVALOS DE PONTEIROS

Alias analysis is one of the most fundamental techniques that compilers use to optimize languages with pointers. However, in spite of all the attention that this topic has received, the current state-of-the-art approaches inside compilers still face challenges regarding precision and speed. In particular, pointer arithmetic, a key feature in C and C++, is yet to be handled satisfactorily. This work presents a new alias analysis algorithm to solve this problem. The key insight of our approach is to combine alias analysis with symbolic range analysis. This combination lets us disambiguate elds within arrays and structs, e ectively achieving more precision than traditional algorithms. To validate our technique, we have implemented it on top of the LLVM compiler. Tests on a vast suite of benchmarks show that we can disambiguate several kinds of C idioms that current state-of-the-art analyses cannot deal with. In particular, we can disambiguate 1.35x more queries than the alias analysis currently available in LLVM. Furthermore, our analysis is very fast: we can go over one million assembly instructions in 10 seconds.
Development of CHF Mapping Method for Fin Structured Surface

Several factors have been identified to affect CHF enhancement: wettability, surface roughness, porosity, surface structure and so on. In this study, we performed CHF experiments using structured surfaces to validate the parameter effects and to understand their physical meanings. Experimental results show that the CHF has a peak value as fin geometry change. A fin with 0.5mm height produces a largest CHF around 1.9MW/m, and fins longer than 2mm reduced CHF values. To explain the results, we developed a CHF mapping method describing liquid supply-side and demand-side limits. The liquid demand-side limit is governed by heat removal capability, mainly nucleates boiling at the heating surface and calculated using the hot spot model. We consider 3 liquid supply-side limiting mechanisms limiting liquid supply to the heating surface: capillary limit in the fin structure and CCFLs in the fin structure and free volume. The capillary limit is determined by balancing capillary pressure and viscous dissipation in liquid film on the fin side. The CCFL in the structure is calculated using a Wallis-type correlation. The CCFL in the free volume limits liquid downward flow by the vapor jetting from the heating surface. The CHF map drawn for our experimental results describes the CHF trend in the water pool successfully. Also, we show that the CHF mapping method well explain the experimental trend in terms of fin length using FC-72 as a bulk liquid. As a result, it is proven that the CHF mapping is an effective way of explaining the CHF in a pool boiling.
ON THE THEORETICAL DEVELOPMENT OF NEW CREEP RESISTANT ALLOYS AND THEIR EMPIRICAL VALIDATION

In anticipation to the present revival of nuclear power, and to obtain more efficient, secure and environmentally-friendly power plants, new families of high temperature resistant, low activation materials are under development. This work presents an example of work performed at CEA during the development of novel ferrito-martensitic reduced activation alloys for Generation IV and Fusion applications. In the past, the process of designing a new material was mostly heuristic, requiring repeated experimental trial and error, but nowadays, synergies between the accuracy of current scientific knowledge in thermodynamics and transformation kinetics and increased computer capacity enables us to design successful new alloys using minimal empirical feedback. This work presents this comprehensive and multi-model approach to alloy and microstructure design. The CALPHAD method, thermo-kinetic modelling of precipitation reactions and artificial neural network analysis are combined in the development of new alloys having their compositions and microstructures optimised for maximum creep resistance. To complete this work, a selection of the alloys designed have been cast and the results obtained during alloy design and the modelling of various heat treatments have been verified. Optical and electronic microscopy have been used to characterise the microstructure. Uniaxial tensile tests have been used to measure the mechanical performance of the alloys presented at room, service and higher temperatures. The characterisation of the behaviour of the material in service conditions is underway with relaxation and creep tests.
Thermal Stratification and Mixing in a Large Pool Induced by Operation of Spargers , Nozzles , and Blowdown Pipes Final Report from the NKS-R COPSAR activity ( Contract : NKS _ R _ 2015 _ 114 )

In a Boiling Water Reactor, steam released from primary coolant system is condensed in the pressure suppression pool. Thermal stratification in the pool affects pressure suppression capacity of the pool. Heat and momentum sources generated by the steam condensation define pool behavior. Direct Contact Condensation (DCC) of steam present a challenge for contemporary modeling tools. In previous work, the Effective Heat Source (EHS) and Effective Momentum Source (EMS) models were proposed to simulate development of thermal stratification or mixing induced by steam injection into a large pool of water. These models are computationally efficient and sufficiently accurate in resolving the effect of DCC phenomena on the large scale pool circulation. In this work, we present the validation of the EHS/EMS models for spargers and mixing nozzles. Validation results with EHS/EMS implemented in GOTHIC and ANSYS Fluent show a good agreement in comparison to the PPOOLEX experiments. The scaling of the PPOOLEX experiments with mixing nozzles was done to preserve prototypical ranges of injection conditions and pool regimes. The experimental results are similar to the pre-test analysis data. An implementation of the EHS/EMS models for analysis of steam injection into a containment pool was developed. The results of analysis provide a realistic pool behavior. Modeling of direct steam injection showed that without EHS/EMS models the results are severely affected by numerical instabilities.
FUZZY CONTROLLER BASED LOW COST HIGH EFFICIENCY CONVERTER FOR AUTONOMOUS PHOTOVOLTAIC WATER PUMPING SYSTEM

This paper proposes a low cost converter for autonomous photovoltaic water pumping system based on fuzzy controller. The proposed converter i.e. the two inductor boost converter achieves ZVS/ZCS conditions.The operation of two inductor boost converter along with the three phase inverter and three phase induction motor is described.The classic topology of the TIBC has features like high voltage gain and low input current ripple. A solar tracking system is modeled using Matlab/Simulink and a fuzzy logic control is designed to control the duty cycle of TIBC.Simulation results show a power output 210w and efficiency of 98%is achieved for DCDC converter.
Regulating Privacy Online: An Economic Evaluation of the GDPR

Modern websites rely on personal data to design better content and to market themselves. The European Union’s General Data Protection Regulation (GDPR) was intended to make access to such personal data more difficult, with the goal of protecting user privacy. We examine the GDPR's impact on website page views and revenue for 1,084 online firms using data from Adobe's website analytics platform. We find a reduction of 12 percent in both EU user website page views and website revenue recorded by the platform after the GDPR’s enforcement deadline. We decompose these GDPR effects into changes in real outcomes and changes to data recording, respectively. (JEL D83, K24, L51, L86, L88, M31, M37)
Effect of CaF 2 addition on the densification and the foaming of sintered glass ‐ ceramics by metallurgical

In this study the possibility to use metallurgical slag from Egyptian company “Helwan” for the production of self-glazing sintered glass-ceramics or glass-ceramic foams is discussed. In details is highlighted the effect of CaF2 addition (in amounts of 0, 2.5, 5 and 7.5 wt %) on the glass melting, densification and foaming processes. The sintering and the bloating trends are evaluated by hot stage microscopy, HSM, using different heating rates and fraction sizes. The phase formation is estimated by X-ray diffraction, XRD, and scanning electron microscopy, SEM. The densities, the porosities and the structures of some of obtained samples are studied by gas pycnometry and mercury intrusion porosimetry. The results demonstrate that the studied glass powders are characterized by good sinter ability in the interval 800-950oC and subsequent intensive bloating in the range 1050-1150oC. The increasing of CaF2 amount in the batches leads to a notable decrease of both melting and sintering temperatures. However, the maximal addition of 7.5 % leads to some reduction of the densification and foaming trends, which is consequence of more intensive liquid-liquid immiscibility and phase formation. Notwithstanding, self-glazed glass-ceramic with high percentage of CaF2 and improved micro-hardness and crystallinity can be obtained by using finer glass powders, moderate heating rates and holding temperatures of 950-1000 C. At the same time, glass-ceramics foams with huge closed porosity of about 80 vol % can be synthesized using glass powders without or with modest addition of CaF2 applying higher heating rates and holding temperatures of 1100-1150 C.
Biophysical Parameters and Actual Evapotranspiration of Bean Culture by Means of Remote Sensing

Agricultural irrigation is involved in an important chain that involves all sectors of the economy, either directly, by increasing food production, or indirectly, by withdrawing large amounts of fresh water. The relevance of this theme forces the search for alternatives to make water use as rational as possible. Evapotranspiration estimation methods based in remote sensing, such as the SAFER (Simple Algorithm for Evapotranspiration Retrieving) model, become extremely relevant in these scenarios, since it is possible to estimate this parameter in large scales. Therefore, the aim of this research was to apply the SAFER model in the estimation of bean crop actual evapotranspiration using Landsat-8 satellite image data. One of the parameters used as input in the SAFER model is the NDVI (Normalized Difference Vegetation Index), which presented a coefficient of determination (r²) equal to 0.80 when compared to the crop coefficient. The actual evapotranspiration (ETa) estimated by the SAFER model were compared to the FAO 56 model estimates for later correlation between the models. This information is expected to assist the producer in a better management of water resources used in irrigation. The correlation between the two models presented a relevant coefficient of determination (r2 = 0.73), representing the potential of the SAFER model in relation to the FAO model 56.
Semantic Clues for Novel Metaphor Generator

In this position paper we introduce our early findings drawn from a new study on an over 30,000 entries collection of metaphorical expressions manually extracted from Japanese literature. Such thoroughly chosen data assure higher standards when figurative speech is analysed from the generation perspective and allow to develop an algorithm for explaining difficult or new notions. Such function is going to be implemented in our artificial tutor project and here we describe a method for generating similes. We also show some statistical discoveries in the semantic level that could be useful knowledge for a dialog system with extended explanation capabilities.
MagicalHands: Mid-Air Hand Gestures for Animating in VR

We explore the use of hand gestures for authoring animations in virtual reality (VR). We first perform a gesture elicitation study to understand user preferences for a spatiotemporal, bare-handed interaction system in VR. Specifically, we focus on creating and editing dynamic, physical phenomena (e.g., particle systems, deformations, coupling), where the mapping from gestures to animation is ambiguous and indirect. We present commonly observed mid-air gestures from the study that cover a wide range of interaction techniques, from direct manipulation to abstract demonstrations. To this end, we extend existing gesture taxonomies to the rich spatiotemporal interaction space of the target domain and distill our findings into a set of guidelines that inform the design of natural user interfaces for VR animation. Finally, based on our guidelines, we develop a proof-of-concept gesture-based VR animation system, MagicalHands. Our results, as well as feedback from user evaluation, suggest that the expressive qualities of hand gestures help users animate more effectively in VR.
bservation of the side chain O-methylation of glutamic acid or spartic acid containing model peptides by electrospray onization-mass spectrometry

O-methylation of the side chains of glutamic acid (E) and aspartic acid (D) residues is generally observed modification when an acidified methanol/water (MeOH/dH2O) mixture is used as a solvent system during sample preparation for proteomic research. This chemical modification may result misidentification with endogenous protein methylation; therefore, a special care should be taken during sample handling prior to mass spectrometric analysis. In the current study, we systematically examined the extent of E/D methylation and C-terminus carboxyl group of synthetic model peptides in terms of different incubation temperatures, storage times, and added acid types as well as its percentages. To monitor these effects, C-terminus amidated and free acid forms of synthetic model peptides comprised of E or D residue(s) have been analyzed by electrospray ionization-mass spectrometry (ESI-MS). Additionally, LC–MS/MS experiments were performed to confirm the formation of methylated peptide product. The results showed that the rate of methylation was increased as the temperature increases along with prolong incubation times. Moreover, the extent of methylation was remarkably high when formic acid (FA) used as a protonation agent instead of acetic acid (AA). In addition, it was found that the degree of methylation was significantly decreased by lowering acid percentages in ESI solution. More than one acidic residue containing model peptides have been also used to explore the extent of multiple methylation reaction. Lastly, the ethanol (EtOH) and isopropanol (iPrOH) have been substituted separately with MeOH in sample preparation step to investigate the extent of esterification reaction under the same experimental conditions. However, in the positive perspective of view, this method can be used as a simple, rapid and cheap method for methylation of acidic residues under normal laboratory conditions. © 2017 Elsevier B.V. All rights reserved.
MEAN SQUARED ERROR REDUCTION FOR GMM ESTIMATORS OF LINEAR TIME SERIES MODELS

In this paper we analyze Generalized Method of Moments (GMM) estimators for time series models as advocated by Hansen and Singleton. It is well known that these estimators achieve efficiency bounds if the number of lagged observations in the instrument set goes to infinity. A new version of the GMM estimator based on kernel weighted moment conditions is proposed. Higher order asymptotic expansions are used to obtain optimal rates of expansions for the number of instruments to minimize the asymptotic Mean Squared Error (MSE) of the estimator. Estimates of optimal bandwidth parameters are then used to construct a fully feasible GMM estimator where the number of lagged instruments are endogenously determined by the data. Expressions for the asymptotic bias of kernel weighted GMM estimators are obtained. It is shown that standard GMM procedures have larger asymptotic biases than kernel weighted GMM. A bias correction for the estimator is proposed. It is shown that the bias corrected version achieves a faster rate of convergence of the higher order terms of the MSE than the uncorrected estimator. An alternative to direct bias correction are k-class estimators introduced by Nagar. This approach is adapted to the time series case. The time series k-class estimator also corrects for the largest order bias and achieves an accelerated rate of convergence for the higher order asymptotic terms.
Physical Activity and Sitting Time in Bariatric Patients Pre-and Post-Surgery

Purpose: Sedentary time, or prolonged sitting/lying time, is an emerging risk factor for severe obesity, independent of physical activity (PA). The purpose of this study was to characterize ambulatory PA as well as sitting/lying time using accelerometry before and after bariatric surgery. Material and methods: Seventeen participants (58.5% female) with a mean age of 46.5 ± 10.1 years, and a Body Mass Index (BMI) of 48.8 ± 6.2 kg/m2 scheduled for bariatric surgery were included in the analysis. ActivPALTM tri-axial accelerometers were attached to the participants’ mid-thigh and worn for 24 hours a day for up to seven consecutive days before surgery, and at three, and six months following bariatric surgery. Mean steps, transitions from sitting-to-standing, as well as standing, walking and sitting/lying time per 24 hours were measured. Results: Prior to bariatric surgery, participants spent 18.6 ± 1.5 hours per 24 hours sitting/lying, representing over 75% of their day. Total sitting/lying time per 24 hours did not change at three or six months after surgery. Baseline accumulated steps per day averaged 6139 ± 2720 and did not change over time. Conclusions: Given that PA and sitting/lying time per 24 hours are believed to independently contribute to energy balance and health outcomes, clinicians and health professionals should intervene more rigorously to simultaneously reduce daily sitting time and increase levels of PA to help bariatric patients successfully manage their weight over the long-term post-surgery.
In-network Principal Component Analysis and Diffusion Strategies

Principal component analysis is a very well-known statistical analysis technique. It determines principal axes that allow relevant data reduction. Thus, it is very useful in networks where a large number of measures is performed. However, such a technique needs high-complexity computation, which does not scales well in large networks. This paper proposes to overcome this issue, by describing several in-network strategies that estimate the principal axes with lower computational complexity. These strategies are either noncooperative or cooperative with information diffusion. The performance of the proposed strategies are illustrated on diverse applications, such as image processing and dimensionality reduction of time series in wireless sensor networks. Index Terms Principal component analysis, network, adaptive learning, distributed processing, dimensionality reduction.
IBMP 3-1 Effect of Exogenous Polyamines on Some Physiological Characteristic and Carbohydrate Metabolism in Rice ( Oryza sativa L . ) Under Drought Stress

Drought stress is the main environmental problems decreasing growth and metabolic processes of rice. This research aimed to study the effects of exogenous polyamines on some physiological characteristic and carbohydrate metabolism in rice seedlings cv. Khao Dawk Mali 105 (Oryza sativa L.) under drought stress. Three polyamines were studied including putrescine, spermidine and spermine. Seedlings were grown for 14 days and foliar sprayed with 300 ml of 10 μM Spd, Spm and Put for 2 days. Irrigation was withheld for 7 days except in control group which was watered daily. The results showed that Spm and Put slightly improved seedling growth under drought stress but was not significantly different. In addition, Spm and Put also increased relative water content and reduced electrolyte leakage. PAs also increased sugar accumulation of plants under stress. These results suggested that PAs can alleviate the effects of drought stress by increasing sugar accumulation in rice.
PRODUCTS IN THE ATIYAH-HIRZEBRUCH SPECTRAL SEQUENCE AND THE CALCULATION OF AfSO,

It is possible to put a multiplicative structure in the Atiyah-Hirzebruch spectral sequence in certain cases even though the spectra involved are not both ring spectra. As a special case, an easy calculation of the homotopy of MSO is obtained. It is the purpose of this paper to give a calculation of the oriented bordism ring MSOt based on some rather elementary considerations. In particular, we recover Wall's result [11] from arguments with the Atiyah-Hirzebruch spectral sequence and the Hurewicz homomorphism for MOt. We introduce products in the Atiyah-Hirzebruch homology spectral sequence under rather mild conditions. These are weak enough to include the case of MSO A X sa MO where X is a spectrum with SX sa ÄP°°. (In particular, X is not a ring spectrum.) We will operate in a suitable category of spectra (e.g., [1] or [6]), which we will not make explicit. All ring spectra will be assumed to be homotopy commutative and homotopy associative and the unit and product maps will be assumed to be cellular. 1. We begin by discussing multiplicative structure in the Atiyah-Hirzebruch spectral sequence [1]. Recall that for given spectra X and Y, there is a spectral sequence {EJq} defined with K,q = "/+,(*' A Y, X"' A Y), D„ = «£,(*' A Y) satisfying (a) E2q ^ Hp(X; ^qs(Y)), (b) 4V ei, Ej_r,q+r_x, H(E'p,q, djj « ¿r;;\ (c) TTp + q(X A Y) is filtered by subgroups F> = im{w*+¿X' AY)-* *p\g(X A Y)} and F'/F"'1 m E~,. We assume that X and Y are connective spectra. We will now further assume that 1. Y and X /\ Y are ring spectra. Received by the editors June 5, 1979 and, in revised form, October 2, 1979. 1980 Mathematics Subject Classification. Primary 57R75. © 1980 American Mathematical Society 0002-9947/80/0000-03S9/$03.2 5
Static Detection of Address Leaks

Taint analysis is a form of program analysis that determines if values produced by unsafe sources might flow into sensitive functions. In this paper we use taint analysis to establish if an adversary might discover the address of any program variable at runtime. The knowledge of an internal program address seems, in principle, a harmless information; however, it gives a malicious user the means to circumvent a protection mechanism known as address space layout randomization, typically used in modern operating systems to hinder buffer overflow attacks, for instance. We depart from previous taint analyses because we also track indirect information leaks, in which confidential data is first stored in memory, from where it flows into some sensitive operation. We have implemented our analysis into the LLVM compiler and have used it to report 204 warnings in a test suite that contains over 1.3 million lines of C code, and includes traditional benchmarks such as SPEC CPU 2006. Our current implementation reduces by more than 14 times the number of sensitive operations that a developer would have to inspect in order to find address leaks manually. Furthermore, our analysis is remarkably efficient: it has been able to process more than 8.2 million assembly instructions in 19.7 seconds!
Using Machine Learning and Deep Learning Methods to Find Mentions of Adverse Drug Reactions in Social Media

Over time the use of social networks is becoming very popular platforms for sharing health related information. Social Media Mining for Health Applications (SMM4H) provides tasks such as those described in this document to help manage information in the health domain. This document shows the first participation of the SINAI group. We study approaches based on machine learning and deep learning to extract adverse drug reaction mentions from Twitter. The results obtained in the tasks are encouraging, we are close to the average of all participants and even above in some cases.