Miracle-dz/UniFAR-FTUs huggingface dataset:
Corporate Governance and State Expropriation Risk

Recent studies show that the transfer of corporate governance structure across borders has significant valuation consequences. It is equally important to consider the valuation effect of state expropriation risk as well as its interaction with quality of corporate governance. Using a sample of cross-border acquisitions during 1989–2009, we find that targets, which operate under some degree of state expropriation risk, receive a significantly lower premium. The target shareholders are not fully rewarded for the improvement in firm governance since the benefits of improvement are mitigated under predation. Our results provide evidence for twin-agency theory of Stulz (2005) through cross-border mergers.
Pure Petri Nets for Software Verification and Validation of Semantic Web Services in Graphical Worlds

Software verification and validation (SVV) are major ingredients of current software engineering projects. Among the available methods to solve this problem, formal methods (although very costly at the computational level) are arguably the most powerful ones. One of the most promising approaches in this field is that based on Petri nets. This paper discusses some issues regarding the application of Petri nets to SVV from a hybrid mathematical/computational point of view. The paper also describes a Mathematica package developed by the author for a class of Petri nets, which is applied to address the SVV problem in the context of graphical semantic web services based on virtual agents evolving in digital 3D worlds.
Fast Frequency Selective Keyhole MRI using Optimized K-Space Trajectories

We present a new Fast Frequency Selective Keyhole (FFSK) method, which allows dynamic acquisition of a low-resolution image signal from the arbitrarily chosen k-space points and reduces acquisition time of the conventional keyhole approach. Off-resonance components are eliminated by the filtering procedure which substantialy increase SNR. The effect of the FFSK method on contrast in dynamic MRI is evaluated.
Caloric restriction stimulates autophagy in rat cortical neurons through neuropeptide Y and ghrelin receptors activation

Caloric restriction is an anti-aging intervention known to extend lifespan in several experimental models, at least in part, by stimulating autophagy. Caloric restriction increases neuropeptide Y (NPY) in the hypothalamus and plasma ghrelin, a peripheral gut hormone that acts in hypothalamus to modulate energy homeostasis. NPY and ghrelin have been shown to be neuroprotective in different brain areas and to induce several physiological modifications similar to those induced by caloric restriction. However, the effect of NPY and ghrelin in autophagy in cortical neurons is currently not known. Using a cell culture of rat cortical neurons we investigate the involvement of NPY and ghrelin in caloric restriction-induced autophagy. We observed that a caloric restriction mimetic cell culture medium stimulates autophagy in rat cortical neurons and NPY or ghrelin receptor antagonists blocked this effect. On the other hand, exogenous NPY or ghrelin stimulate autophagy in rat cortical neurons. Moreover, NPY mediates the stimulatory effect of ghrelin on autophagy in rat cortical neurons. Since autophagy impairment occurs in aging and age-related neurodegenerative diseases, NPY and ghrelin synergistic effect on autophagy stimulation may suggest a new strategy to delay aging process.
Ensemble of Artificial Neural Networks for studying Molecular Markers

Ensembles are well-established as methods for obtaining highly accurate classifiers by combining less accurate ones [1]. An ensemble consists of a set individual predictors that are combined to improve the overall perfomance achieves. Bagging [2] and Boosting [3] are methods frequently used to assemble the ensembles. This work investigates the aplication of Bagging and Boosting, using its version AdaBoostM1 [4] to analyse molecular markers. The use of molecular markers allows the inference of a fenotype from a given genotype [5]. This work investigates the use of Articial Neural Networks as individual estimator or in ensembles to analyse the influence of molecular markers in the characteristics of the meat produced in Brazil. It will investigate which markers are more related to the measured fenotypes. The data set used for this work was obtained from the project of Molecular Markers Applied to Meat Production, which was developed at ”Centro de Pesquisas em Pecuária do Sudeste (CPPSEEmbrapa)” under the responsability of Dr. Luciana de Almeida Regitano. The data was obtained from animals generated from the crossing of Nellore cows whith Aberdeen Angus, Canchim, Simmental and Nellore bulls, born in 1998 and 1999. Data of molecular markers of RFLP (Restriction Fragment Lenght Polymorphism)type and microsattelites were obtained, together with production characteristics, such as weight and carcass composition.
Cross-Platform Analysis of Indirect File Leaks in Android and iOS Applications

Today, much of our sensitive information is stored inside mobile applications (apps), such as the browsing histories and chatting logs. To safeguard these privacy files, modern mobile systems, notably Android and iOS, use sandboxes to isolate apps' file zones from one another. However, we show in this paper that these private files can still be leaked by indirectly exploiting components that are trusted by the victim apps. In particular, we devise new indirect file leak (IFL) attacks that exploit browser interfaces, command interpreters, and embedded app servers to leak data from very popular apps, such as Evernote and QQ. Unlike the previous attacks, we demonstrate that these IFLs can affect both Android and iOS. Moreover, our IFL methods allow an adversary to launch the attacks remotely, without implanting malicious apps in victim's smartphones. We finally compare the impacts of four different types of IFL attacks on Android and iOS, and propose several mitigation methods.
Episodic dependencies and the profitability of moving average strategy on Romanian capital market

Episodic dependencies and moving averages profitability of Romanian capital markets. The evolution of informational efficiency of Romanian stock market is illustrated by means of a test which takes into account nonlinear dynamics. According to this test, we cannot consider a significant amelioration of the efficiency degree of Romanian stock market. Moreover, knowing that random walk are joint tests of the efficiency hypothesis, there was researched the profitability of moving averages on the identified linear and nonlinear correlation sub periods. The results revealed that only nonlinear dependencies are profitably exploited by the moving averages strategies. The most profitable strategy of 15000 strategies was analyzed. The originality of this research is given by the combination of random walk tests with the technical analysis tests, which led to the construction of a new methodology for the evaluation of informational efficiency in weak form.
Free Action as Two Level Voluntary Control

The naturalistic voluntary control (VC) theory explains free will and consciousness in terms of each other. It is central to free voluntary control of action that one can control both what one is conscious of, and also what one is not conscious of. Furthermore, the specific cognitive ability or skill involved in voluntarily controlling whether information is processed consciously or unconsciously can itself be used to explain consciousness. In functional terms, it is whatever kind of cognitive processing occurs when a conscious state is voluntarily chosen. This leads to a bivalent view of cognitive processing in which there is voluntary choice either of non-routine (conscious) or routine (unconscious) kinds of processing. On this VC account, consciousness could not exist without its being possible to voluntarily choose a non-routine kind of processing. But what makes voluntary choice itself possible? The VC theory appeals to the evolutionary inadequacy of a purely low level routine/non-routine (RN) control system that lacks voluntary control. A two level causal system in which a sophisticated upper voluntary level controls the lower RN system offers much more explanatory power and evolutionary fitness. Since the upper level is partly causally independent of the lower level, its decisions are not determined by the lower level-- hence free voluntary control is possible. So both consciousness and free voluntary control must have evolved together.
A Multi-Purpose Model of Conversational Context

Natural language dialogue systems require con-textual information for a variety of processing functions, including reference resolution, speech act recognition, and dialogue management. While much has been written about individual contextual problems, many of the proposed representations are mutually incompatible , unusable by the agents involved in a conversation , or both. We present a model of context that tries to reconcile in a general and systematic fashion the diierences between the discourse models used for reference resolution, conversation act recognition , and dialogue management in a system dealing with conversations. Starting from the technical solutions adopted in DRT, we show rst of all how to obtain a discourse model that while preserving DRT's basic ideas about refer-ential accessibility, includes information about the occurrence of speech acts and their relations. We show then how the information about speech acts can be used to formalize the basic ideas of Grosz and Sidner's model of discourse structure. Finally, we extend this model to incorporate an account of the grounding process. 1 Motivations A vast amount of context is needed to participate in and understand even the simplest conversations. This context includes a large store of (assumed) common knowledge between the participants: about language itself, about conventions of social interaction (e.g., that a question should be responded to with an answer), about the domain of discourse (e.g., that trains move along rail lines, not through the air), as well as more local information shared between just the participants themselves. The individual mental states of the agents are an important element of the context of conversation. And previous utterances in the conversation itself will be important for recognizing and performing appropriate future utterances. This paper is about models of context for systems that engage in naturally occurring conversations. The motivation is provided by work on the TRAINS project at the University of Rochester, one of whose aims is the development of a planning assistant able to engage with its user in spoken conversations in the domain of transportation by train Allen et al., 1995]. The TRAINS prototype must perform at least three kinds of linguistic activities that depend on a context: reference resolution, conversation action recognition and dialogue management. The models of context for reference resolution are typically developed with the aim of making available the antecedents of various the emphasis in the models of context proposed for action recognition and dialogue management has been …
A split-and-merge segmentation algorithm for line extraction in 2D range images

This paper presents a segmentation method for line extraction in 2D range images. It uses a prototype-based fuzzy clustering algorithm in a split-and-merge framework. The split-and-merge structure allows one to use the fuzzy clustering algorithm without any previous knowledge on the number of prototypes. This algorithm aims to be used in mobile robots navigation systems for dynamic map building. Simulation results show its good performance compared to some classical approaches.
Effect of COX-Inhibitors Attentuated LPS Induced Behavioural Alterations in Male Wistar Rats

Sickness behavior appears to be the expression of a central motivational state that reorganizes the organism’s priorities to cope with infectious pathogens.To evaluate the effect of selective and non selective COX inhibitors in lipopolysaccharides induced sickness behaviour,rats were subjected to the forced swim test (FST), open field test,actophotometer. LPS(10mcg/kg i.p). administration increased the immobility period in the FST, and depressed locomotor activity in the actophotometer, decreased line crossing and rearing in open field test, increased body temperature and decreased body weight . COX inhibitors are reported to be effective by reducing the risk of neuro degenerative diseases and sickness behaviours. Rats were pretreated with Non- selective COX inhibitors Aspirin (100&200mg/kg), Selective COX-1 inhibitor Resveratrol(50&100mg/kg) & selective COX-2 inhibitor Celecoxib(10&50mg/kg) for 7 days. At the last day rats were given final injection of saline or Cox inhibitors 30 min prior to LPS (10mcg/kg i.p.). After 120 min of LPS treatment determined the exploratory behaviour in open field test, depression using FST, locomotion using actophotometer, body temperature and body weight. Considering the behavioural and histopathological observations showed in the chronic treatment of Non selective COX inhibitors (aspirin) & selective COX 2 inhibitor (celecoxib) attentuated LPS induced behavioural changes but not in selective COX 1 inhibitor (resveratrol) produced by LPS. Considering that aspirin & Celecoxib attenuates LPS-induced behavioural changes, it is proposed that LPS-induced sickness behavior is dependent on the COX pathway mediate prostaglandins (PGE2)
Portable, efficient, and accurate sampling profiling for java-based middleware

This paper presents innovative program transformations for the efficient and accurate profiling of Java programs. The profiling is based on a deterministic sampling mechanism that exploits the number of executed JVM bytecode instructions to trigger a user-defined profiling agent in order to process samples of the call stack. The instrumentation is entirely portable, profiles are reproducible, and the sampling rate can be dynamically tuned. Moderate overhead and high profile accuracy make the profiling framework attractive for developers of complex systems, such as application servers.
Mechanisms Underlying Greater Sensitivity of Neonatal Cardiac Muscle to Volatile Anesthetics

Background In neonatal heart, plasma membrane Na+–Ca2+ exchange (NCX) and Ca2+ influx channels play greater roles in intracellular Ca2+ concentration [Ca2+]i regulation compared with the sarcoplasmic reticulum (SR). In neonatal (aged 0–3 days) and adult (aged 84 days) rat cardiac myocytes, we determined the mechanisms underlying greater sensitivity of the neonatal myocardium to inhibition by volatile anesthetics. Methods The effects of 1 and 2 minimum alveolar concentration halothane and sevoflurane on Ca2+ influx during electrical stimulation in the presence or blockade of NCX and the Ca2+ channel agonist BayK8644 were examined. [Ca2+]i responses to caffeine were used to examine anesthetic effects on SR Ca2+ release (via ryanodine receptor channels) and reuptake (via SR Ca2+ adenosine triphosphatase). Ca2+ influx via NCX was examined during rapid activation in the presence of the reversible SR Ca2+ adenosine triphosphatase inhibitor cyclopiazonic acid and ryanodine to inhibit the SR. Efflux mode NCX was examined during activation by extracellular Na+ in the absence of SR reuptake. Results Intracellular Ca2+ concentration transients during electrical stimulation were inhibited to a greater extent in neonates by halothane (80%) and sevoflurane (50%). Potentiation of [Ca2+]i responses by BayK8644 (160 and 120% control in neonates and adults, respectively) was also blunted by anesthetics to a greater extent in neonates. [Ca2+]i responses to caffeine in neonates (∼30% adult responses) were inhibited to a lesser extent compared with adults (35 vs. 60% by halothane). Both anesthetics inhibited Ca2+ reuptake at 2 minimum alveolar concentration, again to a greater extent in adults. Reduction in NCX-mediated influx was more pronounced in neonates (90%) compared with adults (65%) but was comparable between anesthetics. Both anesthetics also reduced NCX-mediated efflux to a greater extent in neonates. Potentiation of NCX-mediated Ca2+ efflux by extracellular Na+ and NCX-mediated Ca2+ influx by intracellular Na+ were both prevented by halothane, especially in neonates. Conclusions These data indicate that greater myocardial depression in neonates induced by volatile anesthetics may be mediated by inhibition of NCX and Ca2+ influx channels rather than inhibition of SR Ca2+ release.
Influencing Factors on the Overestimation of Self-Reported Physical Activity: A Cross-Sectional Analysis of Low Back Pain Patients and Healthy Controls

Introduction. The aim of the present study was to determine the closeness of agreement between a self-reported and an objective measure of physical activity in low back pain patients and healthy controls. Beyond, influencing factors on overestimation were identified. Methods. 27 low back pain patients and 53 healthy controls wore an accelerometer (objective measure) for seven consecutive days and answered a questionnaire on physical activity (self-report) over the same period of time. Differences between self-reported and objective data were tested by Wilcoxon test. Bland-Altman analysis was conducted for describing the closeness of agreement. Linear regression models were calculated to identify the influence of age, sex, and body mass index on the overestimation by self-report. Results. Participants overestimated self-reported moderate activity in average by 42 min/day (p = 0.003) and vigorous activity by 39 min/day (p < 0.001). Self-reported sedentary time was underestimated by 122 min/day (p < 0.001). No individual-related variables influenced the overestimation of physical activity. Low back pain patients were more likely to underestimate sedentary time compared to healthy controls. Discussion. In rehabilitation and health promotion, the application-oriented measurement of physical activity remains a challenge. The present results contradict other studies that had identified an influence of age, sex, and body mass index on the overestimation of physical activity.
Performance Analysis of Compressed-Domain Automatic Speaker Recognition as a Function of Speech Coding Technique and Bit Rate

Compressed-domain automatic speaker recognition is based on the analysis of the compressed parameters of speech coders. The objective is to perform low-complexity on-line speaker recognition for VoIP in the compressed domain, without the need to decode or resynthesize the speech bitstream. In this paper, we present initial results in determining the recognition accuracy that can be achieved with five widely used speech coding standards. Experiments with a database of 14 speakers obtain a recognition ratio close to 100% after the analysis of 30 seconds of active speech for most of the considered speech coders and rates. In particular, the results show that performance does not strictly depend on coding rate or codec speech quality
Improving software reliability in data-centered software systems by enforcing composition time constraints

Specifying and enforcing constraints and invariants such as architectural constraints and data typing, strongly enhances the safety and reliability of the software system. Next to design and development constraints, the composition of software systems in component-based software also introduces composition time constraints and dependencies. In data-centered software systems, for example, the software composer implicitly creates dataflow dependencies between software components. Describing composition time constraints and enforcing these constraints at deploy time or at run-time strongly improves the safety and reliability of the software. In this paper, we present an approach for expressing and enforcing dataflow dependencies in data-centered software systems, and conclude with a validation of the approach in a servlet-based case study.
Knowledge as action: A cognitive framework for indoor scene classification

Indoor scene classification is an important topic in computer vision, which is challenging due to the variability of decoration. Human vision system, on the other hand, is marvelous in adaptively recognizing scene categories with excellent performance and can be used for reference. Although bio-inspired computer vision algorithms have proven their effectiveness in classification applications, nowadays few researches on indoor scene classification algorithms attempt to model human vision system, restricting further improvement of performance and making it difficult to achieve adaptive scene understanding. To deal with this problem, in this paper we attempt to model the human vision system and achieve scene classification according to the cognitive theory, by dividing the problem into low-level objection annotation and high-level knowledge inference respectively on a macro perspective. Inspired by the biotical perception principle, a novel cognitive hybrid motivation framework is proposed, including empirical based annotation and inference over knowledge base, which is a simple yet effective framework based on techniques of object detection and classification. For a given indoor scene, objects of indoor scene are first annotated, then knowledge base is utilized to infer the category, reducing the effect of variable background. Environmental context is also utilized to assist classification. The proposed framework are evaluated on popular indoor scene dataset, and its effectiveness is proved by experimental results.
Robust Optimization of Multiple Timing Constraints

Modern field-programmable gate array (FPGA) circuit designs often contain multiple clocks and complex timing constraints, and achieving these constraints requires timing optimization at all stages of the computer-aided design (CAD) flow. To our knowledge, no prior published work has either described or quantitatively evaluated how to compute connection timing criticalities for circuits with multiple timing constraints in order to best guide CAD optimization algorithms. While single-clock techniques have a simple extension to multi-clock circuits, this formulation is not robust for circuits with multiple constraints of different magnitudes, or impossible constraints. We describe a robust method of timing optimization for circuits with multiple timing constraints, implemented in the open-source versatile place and route FPGA CAD tool. Our formulation can optimize multiple constraints well, even in the case where some constraints are impossible, and achieves over 20% greater clock speed with aggressive constraints than a straight-forward extension of single-clock work.
Study of OH-initiated degradation of 2-aminoethanol

Abstract. The degradation of 2-aminoethanol (MEA) by the hydroxyl radical (OH) was studied in the European Photoreactor (EUPHORE), a large outdoor environmental chamber. High-Temperature Proton-Transfer-Reaction Mass Spectrometry (HT-PTR-MS) and Fast Fourier Transform Infrared (FT-IR) were used to follow concentrations of reactants in the gas phase. Aerosol mass concentrations were tracked with Aerosol Mass Spectrometry (AMS). The chamber aerosol model MAFOR was applied to quantify losses of MEA to the particle phase. The rate constant k(OH + MEA) was determined relative to the rate constant of the 1,3,5-trimethylbenzene reaction with OH and was found to be (9.2 ± 1.1) × 10−11 cm3 molecule−1 s−1, and thus the reaction between OH radicals and MEA proceeds a factor of 2–3 faster than estimated by structure-activity relationship (SAR) methods. Main uncertainty of the relative rate determination is the unknown temporal behaviour of the loss rate of MEA to chamber wall surfaces during the sunlit experiments. Nucleation and growth of particles observed in the experiments could be reproduced by the chamber model that accounted for condensation of gaseous oxidation products, condensation of ethanolaminium nitrate and nucleation involving MEA and nitric acid.