Miracle-dz/UniFAR-FTUs huggingface dataset:
N ov 2 00 2 Quantum mechanics and irreversible time flow 1

Time flow has been embodied in time-dependent Schrödinger equation representing one of the foundations of quantum mechanics. Pauli's criticism (1933) has, however, indicated that the assumptions concerning representation Hilbert space have led to some contradictions. Many authors have tried to solve this discrepancy practically without any actual success. The reason may be seen in that two different problems have been mixed: the problem of Pauli (being more general and more important) and non-unitarity of exponential phase operator of linear harmonic oscillator introduced by Dirac, as demonstrated in 1964. The problem will be discussed in a broad historical context and a solution based on extension of representation Hilbert space will be shown. 1. Introduction Time flow in quantum mechanics represented an important problem practically during the whole past century. It is, therefore, necessary to start with a brief survey concerning the beginning of quantum mechanics. This beginning is linked closely with the name of E. Schrödinger (1925, [1]), who believed firmly in wave nature of matter. He proposed his famous wave equation and was successful when he was able to reproduce all main results obtained earlier with the help of Hamilton equations. It was possible to derive all characteristics of a physical system from a wave function Ψ(˜ x, t) where˜x represented coordinates of all matter objects. A great success has been seen in that the discrete atom energy levels have corresponded to eigenvalues of Hamiltonian [2]. The wave function Ψ was interpreted as probability distribution by M. Born [3]. N. Bohr [4] attributed then the probabilistic properties directly to individual matter particles; Heisenberg's [5] uncertainty relations being linked closely with their properties. A further step was done by J. von Neumann [6] who showed that individual Ψ-functions at given t values may be represented by vectors in the Hilbert space spanned on eigenfunc-tions of the corresponding Hamiltonian (determining the total energy of a given physical system). Some additional assumptions have been introduced, however, into the corresponding mathematical model. And Pauli's criticism [7] has concerned just them. Pauli has showed that under the mentioned conditions the time evolution (introduction of the time operator) has required for the Hamiltonian to possess continuous spectrum belonging to the whole real interval (−∞, +∞), which contradicts the necessity of energy being positive (or at least limited from below). This problem has been, however, often related to another one concerning the non-unitarity of exponential phase operator
A Method-Level Analysis of Object-Oriented Techniques in Java Applications

In this paper we seek to provide a foundation for the study of the level of use of object-oriented techniques in Java programs in general, and scientific applications in particular. Specifically, we focus on the use of small methods, and the frequency with which they are called, since this forms the basis for the study of method inlining, an important optimisation technique. We compare the Grande and SPEC benchmark suites, and note a significant difference in the nature and composition of these suites, with the programs from the Grande suite demonstrating a less object-oriented approach. On average, they make less use of the class library than SPEC applications and use longer methods.
Understanding engagement with the privacy domain through design research

This paper reports findings from participatory design research aimed at uncovering how technological interventions can engage users in the domain of privacy. Our work was undertaken in the context of a new design concept, “Privacy Trends”, whose aspiration is to foster technology users' digital literacy regarding ongoing privacy risks and elucidate how such risks fit within existing social, organizational, and political systems, leading to a longer‐term privacy concern. Our study reveals 2 challenges for privacy intervention design: the need to develop technology users' intrinsic motivations with the privacy domain and the importance of framing the concept of privacy within users' interests. Setting our study within a design context enables us to identify 4 design opportunities for fostering engagement with the privacy domain through technology design.
A new taeniolabidoid multituberculate (Mammalia) from the middle Puercan of the Nacimiento Formation, New Mexico, and a revision of taeniolabidoid systematics and phylogeny

Multituberculates were amongst the most abundant and taxonomically diverse mammals of the late Mesozoic and the Palaeocene, reaching their zenith in diversity and body size in the Palaeocene. Taeniolabidoidea, the topic of this paper, includes the largest known multituberculates, which possess highly complex cheek teeth adapted for herbivory. A new specimen from the early Palaeocene (middle Puercan; biochron Pu2) of the Nacimiento Formation, New Mexico represents a new large-bodied taeniolabidoid genus and species, Kimbetopsalis simmonsae. A phylogenetic analysis to examine the relationships within Taeniolabidoidea that includes new information from Kimbetopsalis gen. et sp. nov. and gen. nov. and from new specimens of Catopsalis fissidens, first described here, and data from all other described North American and Asian taeniolabidoids. This analysis indicates that Catopsalis is nonmonophyletic and justifies our transfer of the basal-most taeniolabidoid ‘Catopsalis’ joyneri to a new genus, Valenopsalis. Kimbetopsalis and Taeniolabis form a clade (Taeniolabididae), as do the Asian Lambdopsalis, Sphenopsalis, and possibly also Prionessus (Lambdopsalidae). Taeniolabidoids underwent a modest taxonomic radiation during the early Palaeocene of North America and underwent a dramatic increase in body size, with Taeniolabis taoensis possibly exceeding 100 kg. Taeniolabidoids appear to have gone extinct in North America by the late Palaeocene but the appearance of lambdopsalids in the late Palaeocene of Asia suggests that they dispersed from North America in the early to middle Palaeocene.
Academic Performance and College Dropout: Using Longitudinal Expectations Data to Estimate a Learning Model

We estimate a dynamic learning model of college dropout, taking advantage of unique expectations data to greatly reduce our reliance on standard assumptions. Our simulations show that 45% of dropout in the first 2 years of college can be attributed to what students learn about their academic performance, with this type of learning playing a smaller role later in college. Poorly performing students tend to leave because staying is not worthwhile rather than because they are at risk of failing out of school. Poor performance substantially decreases the enjoyability of school and substantially influences beliefs about postcollege earnings.
Survey of code-size reduction methods

Program code compression is an emerging research activity that is having an impact in several production areas such as networking and embedded systems. This is because the reduced-sized code can have a positive impact on network traffic and embedded system costs such as memory requirements and power consumption. Although code-size reduction is a relatively new research area, numerous publications already exist on it. The methods published usually have different motivations and a variety of application contexts. They may use different principles and their publications often use diverse notations. To our knowledge, there are no publications that present a good overview of this broad range of methods and give a useful assessment. This article surveys twelve methods and several related works appearing in some 50 papers published up to now. We provide extensive assessment criteria for evaluating the methods and offer a basis for comparison. We conclude that it is fairly hard to make any fair comparisons of the methods or draw conclusions about their applicability.
Introduction to Nonlinear Attitude Estimation for Aerial Robotic Systems

A robust and reliable attitude estimator is a key technology enabler for the development of autonomous aerial vehicles. This paper is an introduction to attitude estimation for aerial robotic systems. First, attitude definition and parameterizations are recalled and discussed. Then, several attitude estimation techniques – ranging from algebraic vector observation-based attitude determination algorithms to dynamic attitude filtering and estimation methodologies – are presented and commented upon in relation to practical implementation issues. Particular attention is devoted to the applications of a well-known nonlinear attitude observer (called explicit complementary filter in the literature) to aerial robotics, using a low-cost and light-weight inertial measurement unit, which can be complemented with a GPS or airspeed sensors.
Loss of microsatellite diversity and low effective population size in an overexploited population of New Zealand snapper (Pagrus auratus)

Although the effects of overfishing on species diversity and abundance are well documented, threats to the genetic diversity of marine fish populations have so far been largely neglected. Indeed, there seems to be little cause for concern, as even “collapsed” stocks usually consist of several million individuals, whereas population genetics theory suggests that only very small populations suffer significant loss of genetic diversity. On the other hand, in many marine species the genetically effective population size (Ne), which determines the genetic properties of a population, may be orders of magnitude smaller than the census population size (N). Here, microsatellite analyses of a time series of archived scales demonstrated a significant decline in genetic diversity in a New Zealand snapper population during its exploitation history. Effective population sizes estimated both from the decline in heterozygosity and from temporal fluctuations in allele frequency were five orders of magnitude smaller than census population sizes from fishery data. If such low Ne/N ratios are commonplace in marine species, many exploited marine fish stocks may be in danger of losing genetic variability, potentially resulting in reduced adaptability, population persistence, and productivity.
Systemic Microvascular Dysfunction and Inflammation after Pulmonary Particulate Matter Exposure

The epidemiologic association between pulmonary exposure to ambient particulate matter (PM) and cardiovascular dysfunction is well known, but the systemic mechanisms that drive this effect remain unclear. We have previously shown that acute pulmonary exposure to PM impairs or abolishes endothelium-dependent arteriolar dilation in the rat spinotrapezius muscle. The purpose of this study was to further characterize the effect of pulmonary PM exposure on systemic microvascular function and to identify local inflammatory events that may contribute to these effects. Rats were intratracheally instilled with residual oil fly ash (ROFA) or titanium dioxide at 0.1 or 0.25 mg/rat 24 hr before measurement of pulmonary and systemic microvascular responses. In vivo microscopy of the spinotrapezius muscle was used to study systemic arteriolar responses to intraluminal infusion of the Ca2+ ionophore A23187 or iontophoretic abluminal application of the adrenergic agonist phenylephrine (PHE). Leukocyte rolling and adhesion were quantified in venules paired with the studied arterioles. Histologic techniques were used to assess pulmonary inflammation, characterize the adherence of leukocytes to systemic venules, verify the presence of myeloperoxidase (MPO) in the systemic microvascular wall, and quantify systemic microvascular oxidative stress. In the lungs of rats exposed to ROFA or TiO2, changes in some bronchoalveolar lavage markers of inflammation were noted, but an indication of cellular damage was not found. In rats exposed to 0.1 mg ROFA, focal alveolitis was evident, particularly at sites of particle deposition. Exposure to either ROFA or TiO2 caused a dose-dependent impairment of endothelium-dependent arteriolar dilation. However, exposure to these particles did not affect microvascular constriction in response to PHE. ROFA and TiO2 exposure significantly increased leukocyte rolling and adhesion in paired venules, and these cells were positively identified as polymorphonuclear leukocytes (PMNLs). In ROFA- and TiO2-exposed rats, MPO was found in PMNLs adhering to the systemic microvascular wall. Evidence suggests that some of this MPO had been deposited in the microvascular wall. There was also evidence for oxidative stress in the microvascular wall. These results indicate that after PM exposure, the impairment of endothelium-dependent dilation in the systemic microcirculation coincides with PMNL adhesion, MPO deposition, and local oxidative stress. Collectively, these microvascular observations are consistent with events that contribute to the disruption of the control of peripheral resistance and/or cardiac dysfunction associated with PM exposure.
Contextual Multi-armed Bandits under Feature Uncertainty

We study contextual multi-armed bandit problems under linear realizability on rewards and uncertainty (or noise) on features. For the case of identical noise on features across actions, we propose an algorithm, coined {\em NLinRel}, having $O\left(T^{\frac{7}{8}} \left(\log{(dT)}+K\sqrt{d}\right)\right)$ regret bound for $T$ rounds, $K$ actions, and $d$-dimensional feature vectors. Next, for the case of non-identical noise, we observe that popular linear hypotheses including {\em NLinRel} are impossible to achieve such sub-linear regret. Instead, under assumption of Gaussian feature vectors, we prove that a greedy algorithm has $O\left(T^{\frac23}\sqrt{\log d}\right)$ regret bound with respect to the optimal linear hypothesis. Utilizing our theoretical understanding on the Gaussian case, we also design a practical variant of {\em NLinRel}, coined {\em Universal-NLinRel}, for arbitrary feature distributions. It first runs {\em NLinRel} for finding the `true' coefficient vector using feature uncertainties and then adjust it to minimize its regret using the statistical feature information. We justify the performance of {\em Universal-NLinRel} on both synthetic and real-world datasets.
Theoretical Aspects of the Economic Transition: The Case of Romania

For Romania, as for all other ex-communist countries from Eastern Europe, the transition from the rigid centrally planned economic system to the free-market economy, fair competition based, was an amazing experience. From the academic standpoint, the economic reform was a huge research opportunity, as well as having extremely important practical consequences. Based on the case of Romania, the authors have developed an original, bi-dimensional matrix model of this transition process (Scarlat Model), emphasizing the typology of four basic economic systems. Managerial aspects are underlined – both for economic systems and transition process – as well as some stability considerations. Two features of the transition strategy are presented: the transition path and duration of the process. Special attention was paid to assessing the moment by when the economic transition ends. Analysis of the transition path – based on the theory of deterministic chaos (i.e. short-run predictability) – has led to interesting results: a comprehensive research on the evolution of the Romanian currency exchange over a period of sixteen years (1990–2005) revealed three intervals in the Romanian recent history of economic transition and confirmed the diagnostic of transition end. The general model is applied in the case of Romania and some interesting findings are presented, but it is also fully applicable to all Eastern European countries and not only Romania. The EU accessing process is a different type of transition – rigorously planned, regulated and monitored.
Bayesian Modeling of School Effects Using Hierarchical Models with Smoothing Priors

We describe a new and flexible framework for modeling school effects. Like previous work in this area, we introduce an empirical model that evaluates school performance on the basis of student level test-score gains. Unlike previous work, however, we introduce a flexible model that relates follow-up student test scores to baseline student test scores and explore for possible nonlinearities in these relationships.Using data from High School and Beyond (HSB) and adapting the methodology described in Koop and Poirier (2004a), we test and reject the use of specifications that have been frequently used in research and as a basis for policy. We find that nonlinearities are important in the relationship between intake and follow-up achievement, that rankings of schools are sensitive to the model employed, and importantly, that commonly used specifications can give different and potentially misleading assessments of school performance. When estimating our preferred semiparametric specification, we find small but ``significant'' impacts of some school quality proxies (such as district-level expenditure per pupil) in the production of student achievement.
1 H-MRS quantification of tNA and tCr in patients with multiple sclerosis : a meta-analytic review

Meta-analysis was performed on the results of 75 comparisons from the 30 peer-reviewed publications that used proton magnetic resonance spectroscopy (H-MRS) or spectroscopic imaging to (i) quantify the mean concentrations of total creatine (tCr, found in neurons, astrocytes and oligodendrocytes), and/or total N-acetyl groups (tNA, found only in neurons), in the lesional and/or non-lesional white matter (WM) and/or the grey matter (GM) of patients with multiple sclerosis (MS) and (ii) compare these values with those in the homologous tissues of normal controls (NC). For mean [tNA] values, there was (i) a large-effect-sized overall decrease in patients’ lesional WM relative to NC WM (25 comparisons), (ii) a medium-effect-sized overall decrease in patients’ non-lesional WM relative to NC WM (36 comparisons) and (iii) a medium-effect-sized overall decrease in patients’ GM relative to NC GM (14 comparisons). Patients’ mean [tNA] values were sometimes statistically normal but were never statistically increased. For mean [tCr] values, there was (i) no statistically significant overall change in the patients’ lesional WM relative to NC WM (24 comparisons), although statistically significant increases and decreases were sometimes found, (ii) a medium-effect-sized overall increase in patients’ non-lesional WM relative to NC WM (33 comparisons) and (iii) no statistically significant overall change in patients’ GM relative to NC GM (12 comparisons), although a significant decrease was found in one comparison. Of 41 comparisons with statistically significant changes, 38 combined in a way that would probably result in decreased mean [tNA]/[tCr] ratios such that (i) 66% had statistically decreased mean [tNA] and statistically unchanged mean [tCr] values, (ii) 13% had statistically decreased mean [tNA] and statistically increased mean [tCr] values and (iii) 21% had statistically unchanged mean [tNA] values and statistically increased mean [tCr] values. Of the 25 comparisons that came from studies that also analysed [tNA]/[tCr] ratios, the direction of change in mean [tNA] values and mean [tNA]/[tCr] ratios was concordant in 84%. In comparisons that quantified both [tNA] and [tCr], there was a similar amount of variability in both measures in each of the different tissue types studied, both in patients and NCs. Together, these results suggest that within-voxel tNA/tCr ratios can be interpreted as valid and accurate surrogate measures of ‘cerebral tissue integrity’—with decreased tNA/tCr ratios indicating some combination of neuroaxonal disturbance, oligodendroglial disturbance, and astrocytic proliferation. These results also suggest that, although within-voxel tNA/tCr ratios are not perfect indicators of [tNA] content, they do represent a practical compromise to acquiring surrogate measures of within-voxel neuroaxonal integrity.
Long-Term Outcome of Patients Followed by Nephrologists after an Acute Tubular Necrosis Episode

Aims of our study were to describe the long-term survival in patients surviving an acute tubular necrosis (ATN) episode and determine factors associated with late mortality. We performed a prospective cohort study that evaluated the long-term outcome of 212 patients surviving an ATN episode. Mortality at the end of followup was 24.5%, and the probability of these patients being alive 5 years after discharge was 55%. During the followup, 4.7% of patients needed chronic dialysis. Univariate analysis showed that previous CKD (P = 0.0079), cardiovascular disease (P = 0.019), age greater than 60 years (P < 0.0001), and higher SCr baseline (P = 0.001), after 12 months (P = 0.0015) and 36 months (P = 0.004), were predictors of long-term mortality. In multivariate analysis, older age (HR = 6.4, CI 95% = 1.2–34.5, P = 0.02) and higher SCr after 12 months (HR = 2.1, 95% CI 95% = 1.14–4.1, P = 0.017) were identified as risk factors associated with late mortality. In conclusion, 55% of patients surviving an ATN episode were still alive, and less than 5% required chronic dialysis 60 months later; older age and increased Scr after 12 months were identified as risk factors associated with late death.
Learning to Prevent Inactive Student of Indonesia Open University

The inactive student rate is becoming a major problem in most open universities worldwide. In Indonesia, roughly 36% of students were found to be inactive, in 2005. Data mining had been successfully employed to solve problems in many domains, such as for educational purposes. We are proposing a method for preventing inactive students by mining knowledge from student record systems with several state of the art ensemble methods, such as Bagging, AdaBoost, Random Subspace, Random Forest, and Rotation Forest. The most influential attributes, as well as demographic attributes (marital status and employment), were successfully obtained which were affecting student of being inactive. The complexity and accuracy of classification techniques were also compared and the experimental results show that Rotation Forest, with decision tree as the base-classifier, denotes the best performance compared to other classifiers.
Rule Extraction for Tree-to-Tree Transducers by Cost Minimization

Tree transducers that model expressive linguistic phenomena often require word-alignments and a heuristic rule extractor to induce their grammars. However, when the corpus of tree/string pairs is small compared to the size of the vocabulary or the complexity of the grammar, word-alignments are unreliable. We propose a general rule extraction algorithm that uses cost functions over tree fragments, and formulate the extraction as a cost minimization problem. As a by-product, we are able to introduce back-off states at which some cost functions generate right-hand-sides of previously unseen left-hand-sides, thus creating transducer rules “on-the-ﬂy”. We test the generalization power of our induced tree transducers on a QA task over a large Knowledge Base, obtaining a reasonable syntactic accuracy and effectively overcoming the typical lack of rule coverage.