Miracle-dz/UniFAR-FTUs huggingface dataset:
From bias to opinion: a transfer-learning approach to real-time sentiment analysis

Real-time interaction, which enables live discussions, has become a key feature of most Web applications. In such an environment, the ability to automatically analyze user opinions and sentiments as discussions develop is a powerful resource known as real time sentiment analysis. However, this task comes with several challenges, including the need to deal with highly dynamic textual content that is characterized by changes in vocabulary and its subjective meaning and the lack of labeled data needed to support supervised classifiers. In this paper, we propose a transfer learning strategy to perform real time sentiment analysis. We identify a task - opinion holder bias prediction - which is strongly related to the sentiment analysis task; however, in constrast to sentiment analysis, it builds accurate models since the underlying relational data follows a stationary distribution. Instead of learning textual models to predict content polarity (i.e., the traditional sentiment analysis approach), we first measure the bias of social media users toward a topic, by solving a relational learning task over a network of users connected by endorsements (e.g., retweets in Twitter). We then analyze sentiments by transferring user biases to textual features. This approach works because while new terms may arise and old terms may change their meaning, user bias tends to be more consistent over time as a basic property of human behavior. Thus, we adopted user bias as the basis for building accurate classification models. We applied our model to posts collected from Twitter on two topics: the 2010 Brazilian Presidential Elections and the 2010 season of Brazilian Soccer League. Our results show that knowing the bias of only 10% of users generates an F1 accuracy level ranging from 80% to 90% in predicting user sentiment in tweets.
Statistical properties of quasi-periodic pulsations in white-light flares observed with Kepler

We embark on a study of quasi-periodic pulsations (QPPs) in the decay phase of white-light stellar flares observed by Kepler. Out of the 1439 flares on 216 different stars detected in the short-cadence data using an automated search, 56 flares are found to have pronounced QPP-like signatures in the light curve, of which 11 have stable decaying oscillations. No correlation is found between the QPP period and the stellar temperature, radius, rotation period and surface gravity, suggesting that the QPPs are independent of global stellar parameters. Hence they are likely to be the result of processes occurring in the local environment. There is also no significant correlation between the QPP period and flare energy, however there is evidence that the period scales with the QPP decay time for the Gaussian damping scenario, but not to a significant degree for the exponentially damped case. This same scaling has been observed for MHD oscillations on the Sun, suggesting that they could be the cause of the QPPs in those flares. Scaling laws of the flare energy are also investigated, supporting previous reports of a strong correlation between the flare energy and stellar temperature/radius. A negative correlation between the flare energy and stellar surface gravity is also found.
Protective effects of nitric oxide synthase 3 and soluble guanylate cyclase on the outcome of cardiac arrest and cardiopulmonary resuscitation in mice*

Objectives:Despite advances in resuscitation methods, survival after out-of-hospital cardiac arrest remains low, at least in part, due to postcardiac arrest circulatory and neurologic failure. To elucidate the role of nitric oxide (NO) in the recovery from cardiac arrest and cardiopulmonary resuscitation (CPR), we studied the impact of NO synthase (NOS3)/cGMP signaling on cardiac and neurologic outcomes after cardiac arrest and CPR. Design:Prospective, randomized, controlled study. Setting:Animal research laboratory. Subjects:Mice. Interventions:Female wild-type (WT) mice, NOS3-deficient mice (NOS3−/−), NOS3−/− mice with cardiomyocyte-specific overexpression of NOS3 (NOS3−/−CSTg), and mice deficient for soluble guanylate cyclase α1 (sGCα1−/−) were subjected to potassium-induced cardiac arrest (9 min) followed by CPR. Cardiac and neurologic function and survival were assessed up to 24 hrs post-CPR. Measurements and Main Results:Cardiac arrest and CPR markedly depressed myocardial function in NOS3−/− and sGCα1−/− but not in WT and NOS3−/−CSTg. Neurologic function score and 24 hrs survival rate was lower in NOS3−/− and sGCα1−/− compared with WT and NOS3−/−CSTg. Detrimental effects of deficiency of NOS3 or sGCα1 were associated with enhanced inflammation of heart and liver and increased cell death in heart, liver, and brain that were largely prevented by cardiomyocyte-restricted NOS3 overexpression. Conclusions:These results demonstrate an important salutary impact of NOS3/sGC signaling on the outcome of cardiac arrest. Myocardial NOS3 prevented postcardiac arrest myocardial dysfunction, attenuated end-organ damage, and improved neurologic outcome and survival. Our observations suggest that enhancement of cardiac NOS3 and/or sGC activity may improve outcome after cardiac arrest and CPR.
Crossprotection against nontuberculous mycobacterial infections by Mycobacterium tuberculosis memory immune T lymphocytes

Adoptive immunization of T cell-deficient recipient mice with M. tuberculosis-specific memory immune T lymphocytes conferred upon these animals the ability to express significantly enhanced resistance both to the homologous infection, and to three strains of nontuberculous mycobacteria. These results support the hypothesis, therefore, that antigenic determinants possessed by the four mycobacterial strains that are relevant to the generation of protective cellular immunity are identical or closely crossreactive.
Relative production of tumour necrosis factor alpha and interleukin 10 in adult respiratory distress syndrome.

BACKGROUND: The adult respiratory distress syndrome (ARDS) may be regarded as an example of an uncontrolled or excessive inflammatory response in which tumour necrosis factor alpha (TNF-alpha) has been proposed to play a central role. Interleukin 10 (IL-10) has been identified as an important regulator of this response. The potential role for IL-10 in this context was investigated by measuring the relative production of IL-10 and TNF-alpha protein in the plasma, bronchoalveolar lavage (BAL) fluid, and alveolar macrophage culture supernatants of patients with, or at risk of developing, ARDS. METHODS: Twenty six patients were studied from three groups at risk of or with ARDS: sepsis (n = 12), multiple trauma (n = 8), and perforated bowel (n = 6). Ten patients had ARDS. Bronchoalveolar lavage and venepuncture were performed within 24 hours of arrival on the intensive therapy unit or of diagnosis of ARDS. IL-10 and TNF-alpha protein were detected in the plasma, BAL fluid, and alveolar macrophage supernatants by sandwich enzyme linked immunoabsorbent assays. RESULTS: The median IL-10 concentrations in the plasma and BAL fluid of patients with ARDS were significantly lower than the concentrations detectable in the plasma (median difference-17.5, 95% CI -52.4 to 1.31, p < 0.05) and BAL fluid of at risk patients (median difference -32.1, 95% CI -47.5 to 2.3, p < 0.05). There was a tendency towards enhanced concentrations of TNF-alpha detectable in the alveolar macrophage supernatants and the BAL fluid of patients with ARDS compared with at risk patients, although this did not reach statistical significance. No difference was observed in the plasma concentrations of TNF-alpha between the two groups. The ratios of TNF-alpha to IL-10 protein in the BAL fluid of patients with ARDS and at risk patients were 3.52 and 0.85, respectively (median difference 1.44, 95% CI 0.07 to 5.01, p < 0.01). There was no difference in alveolar macrophage production of IL-10 between the two groups. CONCLUSIONS: This study highlights the potential importance of the pro-inflammatory versus the anti-inflammatory imbalance in ARDS which may be reflected by the ratio of IL-10 and TNF-alpha in the lung.
The rise of defensive engineering: how personal liability considerations impact decision-making

Abstract Based on a survey of Australian engineers (n = 275) this paper examines the impact of personal liability considerations on engineering decision-making. Almost all respondents who make high-stakes decisions saw questions of liability as having both positive (90%) and negative (87%) impacts. Our analysis shows that awareness of personal liability acts to focus the attention of many engineers on the moral dimension of their work. However, it also encourages more expensive decision-making, inhibition of innovation and professional paralysis. We argue that while personal legal liability is a legitimate way to focus engineers’ attention on the potential impact of their work, a problem arises when decision-makers are held responsible for disasters over which they had little control. The focus then shifts to ‘defensive engineering’ practices that are aimed at limiting individual liability rather than disaster prevention. Legal processes that are seen to unfairly allocate blame do not encourage practices that support future disaster prevention.
Composing Data-Providing Web Services

Today, more than ever, modern enterprises are using Web services for data sharing within and across the enterprise's boundaries. We call this kind of Web service as Data Providing Web services. In this paper, we present our approach to automatically compose primitive data providing Web services for the purpose of creating data integration applications. Our approach exploits existing mature works done in data integration systems. Specifically, data providing services are modeled as RDF Parameterized Views over mediated ontologies. Then, an RDF oriented query rewriting algorithm is used to compose services for answering received queries. The composition is then optimized and deployed as a new Web service accessible on top of the Web.
Determination of Glutamic Acid Decarboxylase (GAD65) in Pancreatic Islets and Its In Vitro and In Vivo Degradation Kinetics in Serum Using a Highly Sensitive Enzyme Immunoassay

Glutamic acid decarboxylase GAD65 autoantibodies (GADA) are an established marker for autoimmune diabetes. Recently, the autoantigen GAD65 itself was proposed as biomarker of beta-cell loss for prediction of autoimmune diabetes and graft rejection after islet transplantation. Therefore, the GAD65 content in pancreatic islets of different species and its serum degradation kinetics were examined in this study using a sensitive immunoassay. GAD65 was found in quantities of 78 (human), 43.7 (LEW.1A rat) and 37.4 (BB/OK rat) ng per 1,000 islets, respectively, but not in mouse islets. The in vitro half-life of porcine GAD65 and human recombinant GAD65 ranged from 1.27 to 2.35 hours at 37°C in human serum, plasma and blood, and was unaffected by presence of GAD65 autoantibodies. After injecting 2,000 ng recombinant human GAD65 into LEW.1A rats, the in vivo half-life was 2.77 hours. GAD65 was undetectable after 24 hours in these animals, and for up to 48 hours following diabetes induction by streptozotocin in LEW.1A rats. Estimated from these data, at least 13 islets in rat and 1,875 in human must be simultaneously destroyed to detect GAD65 in circulation. These results should be taken into consideration in further studies aimed at examining the diagnostic relevance of GAD65.
Short communication Human papillomavirus DNA detection and typing in male urine samples from a high-risk population from Argentina

The aim of the present study was to evaluate the first void urine (FVU) as a non-invasive sampling method for HPV detection and genotyping in a high-risk population. Men presenting with HPV associated penile lesions or HPV positive partners attending a urological department in La Plata, Argentina were enrolled for HPV detection and genotyping. DNA from 185 first-void urine samples was evaluated for the presence of HPV by nested polymerase chain reaction using MY09/11 and GP05/06 primers. The viral genotype was analyzed by means of the single-stranded conformation polymorphisms (SSCP) method. Seventy-three percent (135/185) of the FVU specimens were positive for HPV-DNA. The viral prevalence in patients with HPV-DNA positive partners was 68.8% (77/112), and 79.5% (58/73) of patients with penile lesions were found to be HPV positive. The most frequent viral type was HPV-11 (26.7%), followed by HPV-6 (23%), HPV-16 (21.5%), HPV-18 (6%), and HPV-31 (4.4%). In this study, 11.1% (15/135) of the HPV positive specimens were double infections. These results indicate that high-risk HPVs can be found in clinical lesions in a high percentage (43.8%), as simple or double infections. In this sense, the male population represents an important reservoir for the virus and may play a role in the transmission and perpetuation of the infection in the general population. The method described below provides a tool for detection and typing of HPV-DNA using samples obtained by non-invasive techniques and thus easy to obtain. © 2004 Elsevier B.V. All rights reserved.
Rural China Takes Off: Institutional Foundations of Economic Reform

In this incisive analysis of one of the most spectacular economic breakthroughs in the Deng era, Jean C. Oi shows how and why Chinese rural-based industry has become the fastest growing economic sector not just in China but in the world. Oi argues that decollectivization and fiscal decentralization provided party officials of the localities--counties, townships, and villages--with the incentives to act as entrepreneurs and to promote rural industrialization in many areas of the Chinese countryside. As a result, the corporatism practiced by local officials has become effective enough to challenge the centrality of the national state. Dealing not only with the political setting of rural industrial development, Oi's original and strongly argued study also makes a broader contribution to conceptualizations of corporatism in political theory. Oi writes provocatively about property rights and principal-agent relationships and shows the complex financial incentives that underpin and strengthen the growth in local state corporatism and shape its evolution. This book will be essential for those interested in Chinese politics, comparative politics, and communist and post-communist systems.
DROL: an object-oriented programming language for distributed real-time systems

In this paper, we first characterize distributed real-time systems by the following two properties that have to be supported: best eflorl and leas2 suffering. Then, we propose a distributed real-time object model DRO which complies these properties. Based on the DRO model, we design an object oriented programming language DROL: an extension of C++ with the capa.bility of describing distributed real-time systems. The most eminent feature of DROL is that users can describe on meta level the semantics of message communications as a communication protocol with sending and receiving primitives. With this feature, we can construct a flexible distributed real-time system satisfying specifications which include timing constraints. We implement a runtime system of DROL on the ARTS kernel, and evaluate the efficiency of the prototype implementation as well as confirm the high expressive power of the language.
Percutaneous transluminal angioplasty is feasible and effective in patients on chronic dialysis with severe peripheral artery disease.

BACKGROUND Peripheral arterial disease (PAD) is common among patients on chronic dialysis. Despite severe clinical manifestations, the indication for bypass surgery is controversial, because of the high morbidity and mortality rate of these patients. The less invasive percutaneous transluminal angioplasty (PTA) is a possible alternative, but data about PTA in dialysis patients are scarce. METHODS We followed 107 dialysis patients (mean age 67+/-10, 75 males) with 132 ischaemic limbs (97% with critical limb ischaemia and ischaemic foot lesions or rest pain) consecutively treated by PTA. RESULTS PTA was successful in 97% of cases. Median follow-up was 22 months. Cumulative limb salvage rates at 12, 24, 36 and 48 months were 86, 84, 84 and 62%, respectively. Log-rank test showed an association between major amputation and baseline presence of foot lesions (P=0.04). This association was confirmed by a Cox survival multivariate analysis [hazard ratio (HR)=7.03, 95% confidence interval (CI)=1.1-43.0, P=0.035]. Limb salvage without any new intervention on the same leg was achieved in 70% of the cases, and was associated with the absence of diabetes mellitus (P=0.01), lower number of treated lesions (P=0.04) and proximal level (iliac and/or femoro-popliteal) of PTA (P<0.001). Independent predictors were diabetes mellitus (HR=3.47, 95% CI=1.31-9.17, P=0.01) and proximal PTA (HR=0.28, 95% CI=0.08-0.94, P=0.04). Fifty-three (49%) patients died during follow-up. Patients older than 67 years (the median value in our sample) had a 2.4-fold increase in mortality risk (95% CI=1.4-4.1, P<0.001). CONCLUSIONS PTA is feasible and effective in dialysis patients with PAD, and should be preferred to other more invasive interventions.
Metrics for Evaluation of Ontology-based Information Extraction

The evaluation of the quality of ontological classification is an important part of semantic web technology. Because this area is under constant development, it requires improvement and standardisation. This paper discusses existing evaluation metrics, and proposes a new method for evaluating the ontology population task, which is general enough to be used in a variety of situations, yet more precise than many current metrics. The paper further describes our first eorts in operationalising the evaluation procedure, including the creation of a semantically annotated corpus that will function as a test bed for the proposed evaluation mechanism, and comparison of dierent evaluation metrics. We conclude that for ontology-based evaluation, a more complex mechanism than is traditionally used is preferable. This mechanism aims to drive a benchmarking assessment tool for the current state-of-the-art of ontology population, and to set a standard for best practice for future evaluation of human language technology for the semantic web.
Solving multiobjective Optimal Control problems in space mission design using Discrete Mechanics and reference point techniques

Many different numerical methods have been developed to compute trajectories of optimal control problems on the one hand and to approximate Pareto sets of multiobjective optimization problems on the other hand. However, so far only few approaches exist for the numerical treatment of the combination of both problems leading to multiobjective optimal control problems. In this contribution we combine the optimal control method Discrete Mechanics and Optimal Control (DMOC) with reference point techniques to compute Pareto optimal control solutions. The presented approach is verified by determining a multiobjective optimal transfer for a space mission. Due to the approximation of the Pareto set, structurally different kind of mission trajectories can be detected which would not have been found by local single-objective optimal control methods and provide important information for a mission designer.
The Cores of Dark Matter-dominated Galaxies: Theory versus Observations

We use the rotation curves of a sample of dark matter-dominated dwarf and low surface brightness (LSB) late-type galaxies to study their radial mass distributions. We find that the shapes of the rotation curves are remarkably similar for all (both dwarf and LSB) galaxies in the sample, suggesting a self-similar density distribution of their dark matter (DM) halos. This shape can be reproduced well by a density profile with a shallow central cusp [ρ(r) ∝ 1/rγ, γ ≈ 0.2-0.4] corresponding to a steeply rising velocity curve [v(r) ∝ rg, g ≈ 0.9-0.8]. We further show that the observed shapes of the rotation curves are well matched by the average density profiles of dark matter halos formed in very high resolution simulations of the standard cold dark matter model (CDM), the low-density CDM model with cosmological constant (ΛCDM), and the cold + hot dark matter model with two types of neutrino (CHDM). This is surprising in light of several previous studies, which suggested that the structure of simulated dark matter halos is inconsistent with the dynamics of dwarf galaxies. We discuss possible explanations for this discrepancy and show that it is most likely caused by the systematic differences at small radii between the analytic model proposed by Navarro, Frenk, & White, with γNFW = 1, and the actual central density profiles of the dark matter halos. We also show that the mass distributions in the hierarchically formed halos are on average consistent with the shape of rotation curves of dark matter-dominated galaxies. However, the scatter of the individual profiles around the average is substantial. Finally, we show that the dark matter halos in our hierarchical simulations and the real galaxies in our sample exhibit a similar decrease in their characteristic densities with increasing characteristic radial scales and show increase in their maximum rotation velocities with increase in the radii at which their maximum velocities occur.
Systematic assessment of multi-gene predictors of pan-cancer cell line sensitivity to drugs exploiting gene expression data

Selected gene mutations are routinely used to guide the selection of cancer drugs for a given patient tumour. Large pharmacogenomic data sets were introduced to discover more of these single-gene markers of drug sensitivity. Very recently, machine learning regression has been used to investigate how well cancer cell line sensitivity to drugs is predicted depending on the type of molecular profile. The latter has revealed that gene expression data is the most predictive profile in the pan-cancer setting. However, no study to date has exploited GDSC data to systematically compare the performance of machine learning models based on multi-gene expression data against that of widely-used single-gene markers based on genomics data. Here we present this systematic comparison using Random Forest (RF) classifiers exploiting the expression levels of 13,321 genes and an average of 501 tested cell lines per drug. To account for time-dependent batch effects in IC50 measurements, we employ independent test sets generated with more recent GDSC data than that used to train the predictors and show that this is a more realistic validation than K-fold cross-validation. Across 127 GDSC drugs, our results show that the single-gene markers unveiled by the MANOVA analysis tend to achieve higher precision than these RF-based multi-gene models, at the cost of generally having a poor recall (i.e. correctly detecting only a small part of the cell lines sensitive to the drug). Regarding overall classification performance, about two thirds of the drugs are better predicted by multi-gene RF classifiers. Among the drugs with the most predictive of these models, we found pyrimethamine, sunitinib and 17-AAG.
Cultural Values, CEO Risk Aversion and Corporate Takeovers

We explicitly examine the role of culture in corporate takeover decisions. Prior research suggests that the risk aversion of CEOs affects their takeover decisions. In this paper, we argue that managerial risk aversion at a national level is a cultural trait and affects the net synergies. CEOs of firms located in countries with higher level of risk aversion, measured by Hofstede’s (2001) uncertainty avoidance score, show less takeover activity, engage more in diversifying takeovers and require higher premiums on takeovers. Required net synergies are higher for smaller firms, relatively larger deals, and for firms that engage in more takeover activity. "Keywords: Financial Decision Making; Risk Aversion; Synergies; Culture; Takeovers. " "Classification-JEL: D81; G34; M14. "