Miracle-dz/UniFAR-FTUs huggingface dataset:
Proposal of managerial standards for new product portfolio management in Brazilian pharmaceutical companies

New Product Portfolio Management is aimed at helping decision-makers better select projects for new products based on key criteria for the manufacturer. The Brazilian pharmaceutical industry has been undergoing change due to stricter sanitary requirements following the enactment of the Generic Law in 1999. This paper presents the results of a research study aimed at clarifying the rationale employed by national pharmaceutical companies in selecting and prioritizing their new product development projects. Consequently, proposals for an analytical structure that could help these companies better select their products were produced. The research was carried out using case study methodology in which four different companies were investigated. The results of the field study confirmed that these companies had a non-structured Product Development System and that the selection of new product development projects was made on a non-systematic basis. The research also identified key criteria for the selection of projects of new pharmaceutical products, which provided the basis for the preparation of a proposal for a managerial standard for application of New Product Portfolio Management.
Vector analysis of two-dimensional Ronchi grating in the metrology system

The semiconductor industry is aggressively pushed to produce smaller and smaller feature size from their existing base of lithography system, wavefront aberration should be derived by comparing ideal and real wavefronts at the wafer plane of a high resolution lithography system. In modern optical metrology, shearing interferometer is used more and more widely. We proposed a two-dimensional shearing interferometer, using two-dimensional Ronchi grating instead of a traditional one-dimensional grating, which can realize multidirectional and multidimensional shear. In order to further improve the detection accuracy of metrology system, vector diffraction theory is introduced. By comparing the vector and scalar light field, finally we can get the impact of vector light field on the performance of the shearing interferometer. This is for us to further improve the accuracy of detection system to provide rich information, which is crucial for the development of the lithography process.
Autotuning Skeleton-Driven Optimizations for Transactional Worklist Applications

Skeleton or pattern-based programming allows parallel programs to be expressed as specialized instances of generic communication and computation patterns. In addition to simplifying the programming task, such well structured programs are also amenable to performance optimizations during code generation and also at runtime. In this paper, we present a new skeleton framework that transparently selects and applies performance optimizations in transactional worklist applications. Using a novel hierarchical autotuning mechanism, it dynamically selects the most suitable set of optimizations for each application and adjusts them accordingly. Our experimental results on the STAMP benchmark suite show that our skeleton autotuning framework can achieve performance improvements of up to 88 percent, with an average of 46 percent, over a baseline version for a 16-core system and up to 115 percent, with an average of 56 percent, for a 32-core system. These performance improvements match or even exceed those obtained by a static exhaustive search of the optimization space.
Bank Bailouts: REITs and their Performance as Financial Stock

This study focuses on the implications of bank bailouts on the risk and return performance of REITs and other financial stocks. Previous evidence on monetary policy finds positive value effects on REITs when federal fund rates are decreased in order to strengthen the market’s liquidity pool. Bank bailouts can also be seen as a positive monetary shock to capital markets as government intervention restores bank liquidity and thus market liquidity. However, empirical evidence on moral hazard shows that bailing out banks may increase risky behavior and benefit relatively risky assets. Therefore, we expect REITs as hard assets to underperform the market on a short term basis. In fact we find supporting evidence i.e. negative abnormal returns and beta risk increases for REITs around bank bailout announcements. This extends previous research on bank failures and REIT returns where positive abnormal REIT returns around bank failures identify REITs as a safe haven in times of market uncertainty. Furthermore we complete our research by investigating other financial stocks, finding unique results.
A method for ontologies structures and contents comparison

Growth of an internet information source makes harder to user effective finding relevant information. Search engines and category hierarchical systems deal mainly with human purpose. But if there are the machines for integration or for adaptation used, then some meta-data information (data about data) have to be added to the processed data. There are some possibilities to store the meta-data information - the very effective one is an ontology representation. The ontology (e.g. described in OWL) at least provides a hierarchical concept structure and restrictions for its instances. Ontologies can be integrated (mapped, merged) to a one complex ontology. This integration of ontologies brings many advantages. On the other hand, the integration brings many problems in case when input ontologies are not fully compatible. We want to find conditions for semi-automatic or fully automatic ontology integration.
Cooperative Lattice Coding and Decoding

A novel lattice coding framework is proposed for outage-limited cooperative channels. This framework provides practical implementations for the optimal cooperation protocols proposed by Azarian et al. In particular, for the relay channel we implement a variant of the dynamic decode and forward protocol, which uses orthogonal constellations to reduce the channel seen by the destination to a single-input single-output time-selective one, while inheriting the same diversity-multiplexing tradeoff. This simplification allows for building the receiver using traditional belief propagation or tree search architectures. Our framework also generalizes the coding scheme of Yang and Belfiore in the context of amplify and forward cooperation. For the cooperative multiple access channel, a tree coding approach, matched to the optimal linear cooperation protocol of Azarain et al, is developed. For this scenario, the MMSE-DFE Fano decoder is shown to enjoy an excellent tradeoff between performance and complexity. Finally, the utility of the proposed schemes is established via a comprehensive simulation study.
Functional significance of the emotion-related late positive potential

The late positive potential (LPP) is an event-related potential (ERP) component over visual cortical areas that is modulated by the emotional intensity of a stimulus. However, the functional significance of this neural modulation remains elusive. We conducted two experiments in which we studied the relation between LPP amplitude, subsequent perceptual sensitivity to a non-emotional stimulus (Experiment 1) and visual cortical excitability, as reflected by P1/N1 components evoked by this stimulus (Experiment 2). During the LPP modulation elicited by unpleasant stimuli, perceptual sensitivity was not affected. In contrast, we found some evidence for a decreased N1 amplitude during the LPP modulation, a decreased P1 amplitude on trials with a relatively large LPP, and consistent negative (but non-significant) across-subject correlations between the magnitudes of the LPP modulation and corresponding changes in d-prime or P1/N1 amplitude. The results provide preliminary evidence that the LPP reflects a global inhibition of activity in visual cortex, resulting in the selective survival of activity associated with the processing of the emotional stimulus.
A Canonical Neural Circuit for Cortical Nonlinear Operations

A few distinct cortical operations have been postulated over the past few years, suggested by experimental data on nonlinear neural response across different areas in the cortex. Among these, the energy model proposes the summation of quadrature pairs following a squaring nonlinearity in order to explain phase invariance of complex V1 cells. The divisive normalization model assumes a gain-controlling, divisive inhibition to explain sigmoid-like response profiles within a pool of neurons. A gaussian-like operation hypothesizes a bell-shaped response tuned to a specific, optimal pattern of activation of the presynaptic inputs. A max-like operation assumes the selection and transmission of the most active response among a set of neural inputs. We propose that these distinct neural operations can be computed by the same canonical circuitry, involving divisive normalization and polynomial nonlinearities, for different parameter values within the circuit. Hence, this canonical circuit may provide a unifying framework for several circuit models, such as the divisive normalization and the energy models. As a case in point, we consider a feedforward hierarchical model of the ventral pathway of the primate visual cortex, which is built on a combination of the gaussian-like and max-like operations. We show that when the two operations are approximated by the circuit proposed here, the model is capable of generating selective and invariant neural responses and performing object recognition, in good agreement with neurophysiological data.
Latent Point Process Models for Spatial-Temporal Networks

Social network data is generally incomplete with missing information about nodes and their interactions. Here we propose a spatialtemporal latent point process model that describes geographically distributed interactions between pairs of entities. In contrast to most existing approaches, we assume that interactions are not fully observable, and certain interaction events lack information about participants. Instead, this information needs to be inferred from the available observations. We develop an efficient approximate algorithm based on variational expectationmaximization to infer unknown participants in an event given the location and the time of the event. We validate the model on synthetic as well as real–world data, and obtain very promising results on the identityinference task. We also use our model to predict the timing and participants of future events, and demonstrate that it compares favorably with a baseline approach.
Online face recognition and learning for cognitive robots

For human-robot interaction users have to be robustly identified and their appearances learned online. Existing state of the art methods for face recognition do not support online learning of faces and lack the recognition performance required to be used in real-world situations. Hence a novel method is introduced in this paper as a descriptor, which provides the required performance by increasing the separability of the classes by maximizing the inter-class and minimizing intra-class variations. The robustness against variations in lighting and pose as well as the speed is increased by selecting only the most representative samples. Additionally to allow for classification of unknown faces, a novel method has been introduced. The main benefit over the state of the art methods is finding the relation between the distance of classification and the certainty of that classification. This relation is automatically calculated from the data belonging to each class. In that way novelty detection can be performed. To further improve recognition performance a method has been used that utilizes multiple frames in classification. To prove the benefits of the introduced methods extensive experiments have been performed on a state of the art face recognition database.
Automated detection of confidentiality goals

The security goals of an authentication protocol specify the high level properties of a protocol. Despite the importance of goals, these are rarely specified explicitly. Yet, a qualified analysis of a security protocol requires that the goals are stated explicitly. We propose a novel approach to find confidentiality goals in an automated way, based only on the protocol specification. The benefits of the method are: (i) Manual specification of goals is replaced by fully automated methods, (ii) the algorithm constructs the entire protection domain of a protocol, that is, all private and shared secrets, and (iii) the goal of an attack can be found, explaining which compromised entities are shared between the attacker and the honest principals.
Non-Invasive Brain Stimulation: An Interventional Tool for Enhancing Behavioral Training after Stroke

Stroke is the leading cause of disability among adults. Motor deficit is the most common impairment after stroke. Especially, deficits in fine motor skills impair numerous activities of daily life. Re-acquisition of motor skills resulting in improved or more accurate motor performance is paramount to regain function, and is the basis of behavioral motor therapy after stroke. Within the past years, there has been a rapid technological and methodological development in neuroimaging leading to a significant progress in the understanding of the neural substrates that underlie motor skill acquisition and functional recovery in stroke patients. Based on this and the development of novel non-invasive brain stimulation (NIBS) techniques, new adjuvant interventional approaches that augment the response to behavioral training have been proposed. Transcranial direct current, transcranial magnetic, and paired associative (PAS) stimulation are NIBS techniques that can modulate cortical excitability, neuronal plasticity and interact with learning and memory in both healthy individuals and stroke patients. These techniques can enhance the effect of practice and facilitate the retention of tasks that mimic daily life activities. The purpose of the present review is to provide a comprehensive overview of neuroplastic phenomena in the motor system during learning of a motor skill, recovery after brain injury, and of interventional strategies to enhance the beneficial effects of customarily used neurorehabilitation after stroke.
UvA-DARE ( Digital Academic Repository ) Practical and reliable FRET / FLIM pair of fluorescent proteins

Background: In spite of a great number of monomeric fluorescent proteins developed in the recent years, the reported fluorescent protein-based FRET pairs are still characterized by a number of disadvantageous features, complicating their use as reporters in cell biology and for highthroughput cell-based screenings. Results: Here we screened some of the recently developed monomeric protein pairs to find the optimal combination, which would provide high dynamic range FRET changes, along with high pHand photo-stability, fast maturation and bright fluorescence, and reliable detection in any fluorescent imaging system. Among generated FRET pairs, we have selected TagGFP-TagRFP, combining all the mentioned desirable characteristics. On the basis of this highly efficient FRET pair, we have generated a bright, high contrast, pHand photo-stable apoptosis reporter, named CaspeR3 (Caspase 3 Reporter). Conclusion: The combined advantages suggest that the TagGFP-TagRFP is one of the most efficient green/red couples available to date for FRET/FLIM analyses to monitor interaction of proteins of interest in living cells and to generate FRET-based sensors for various applications. CaspeR3 provides reliable detection of apoptosis, and should become a popular tool both for cell biology studies and high throughput screening assays. Background During the last decade genetically-encoded sensors on the basis of FRET (Förster Resonance Energy Transfer) between fluorescent proteins have become popular instruments to study kinetics and localization of different pathways inside living cells [1,2]. However, their application is limited by relatively low dynamic range (donor/ acceptor emission ratio change), which is limited, in its turn, by FRET efficiency. In addition, spectral separation can be problematic due to pronounced cross-talks characteristic for the traditional cyan and yellow FRET partners. Recent development of orange, red and far-red monomeric fluorescent proteins drastically enriched the palette Published: 25 March 2009 BMC Biotechnology 2009, 9:24 doi:10.1186/1472-6750-9-24 Received: 6 October 2008 Accepted: 25 March 2009 This article is available from: http://www.biomedcentral. com/1472-6750/9/24 © 2009 Shcherbo et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Detecting Lane Departures Using Weak Visual Features

Many current lane departure warning systems rely on strong visual cues, such as distinct lane markings[1][2] or the presence of a leading vehicle[6]. In this project, we propose a system that detects lane departures using only weak visual features derived from dashboard camera footages. In doing so, we aim to build a model that can detect lane departures even on roads with faded or missing lane markings, in inclement weather (e.g. snow-covered roads, fog and heavy rain) and in poor lighting conditions. Our proposed model uses extracted optical flow trajectories[4] of various points in the scene detected using the Shi-Tomasi corner detector[5]. These trajectories are then normalized and featurized using Histogram of Oriented Gradients (HOG). We used SVM with a radial basis function (RBF) kernel to classify these trajectories into one of two categories: straight (vehicle is within the lane) and deviate (vehicle is leaving the lane). Our SVM model is compared against a logistic regression model that provided a performance baseline. Both models produced reasonable results with our SVM model detecting lane departures up to 88% accuracy.
Long-term safety and efficacy of drug-eluting versus bare-metal stents in Sweden.

BACKGROUND The long-term safety and efficacy of drug-eluting coronary stents have been questioned. METHODS We evaluated 47,967 patients in Sweden who received a coronary stent and were entered into the Swedish Coronary Angiography and Angioplasty Registry between 2003 and 2006 and for whom complete follow-up data were available for 1 to 5 years (mean, 2.7). In the primary analysis, we compared patients who received one drug-eluting coronary stent (10,294 patients) with those who received one bare-metal stent (18,659), after adjustment for differences in clinical characteristics of the patients and characteristics of the vessels and lesions. RESULTS Analyses of outcome were based on 2380 deaths and 3198 myocardial infarctions. There was no overall difference between the group that received drug-eluting stents and the group that received bare-metal stents in the combined end point of death or myocardial infarction (relative risk with drug-eluting stents, 0.96; 95% confidence interval [CI], 0.89 to 1.03) or the individual end points of death (relative risk, 0.94; 95% CI, 0.85 to 1.05) and myocardial infarction (relative risk, 0.97; 95% CI, 0.88 to 1.06), and there was no significant difference in outcome among subgroups stratified according to the indication for stent implantation. Patients who received drug-eluting stents in 2003 had a significantly higher rate of late events than patients who received bare-metal stents in the same year, but we did not observe any difference in outcome among patients treated in later years. The average rate of restenosis during the first year was 3.0 events per 100 patient-years with drug-eluting stents versus 4.7 with bare-metal stents (adjusted relative risk, 0.43; 95% CI, 0.36 to 0.52); 39 patients would need to be treated with drug-eluting stents to prevent one case of restenosis. Among high-risk patients, the adjusted risk of restenosis was 74% lower with drug-eluting stents than with bare-metal stents, and only 10 lesions would need to be treated to prevent one case of restenosis. CONCLUSIONS As compared with bare-metal stents, drug-eluting stents are associated with a similar long-term incidence of death or myocardial infarction and provide a clinically important decrease in the rate of restenosis among high-risk patients.
ON THE SELECTION OF IRREGULAR, MISSPECIFIED REGRESSION MODELS : A COMMENT ON FOLKLORE

In this paper we will investigate the consequences of applying model selection methods under regularity conditions that are sufficiently general to encompass (i) stochastic models involving non-stationary processes and (ii) situations where the true structure of the process falls outside the class of models under consideration. The properties of selection criteria that use very general measures of model complexity are considered and the results are used to draw attention to the fallacy of traditional beliefs concerning commonly employed model selection criteria.
Combinatorial Investigation of Spintronic Materials

High-throughput synthesis and characterization techniques have been effective in discovering new materials and performing rapid mapping of phase diagrams. The application of the combinatorial strategy to explore doped transition-metal oxides has led to the discovery of a transparent room-temperature ferromagnetic oxide in Co-doped anatase TiO_2. The discovery has triggered a wave of studies into other metal oxide systems in pursuit of diluted magnetic semiconductors. In this article, we describe recent combinatorial studies of magnetic transition-metal oxides, germanium-based magnetic semiconductors, and Heusler alloys.
Crystal Structures of the Human G3BP1 NTF2-Like Domain Visualize FxFG Nup Repeat Specificity

Ras GTPase Activating Protein SH3 Domain Binding Protein (G3BP) is a potential anti-cancer drug target implicated in several cellular functions. We have used protein crystallography to solve crystal structures of the human G3BP1 NTF2-like domain both alone and in complex with an FxFG Nup repeat peptide. Despite high structural similarity, the FxFG binding site is located between two alpha helices in the G3BP1 NTF2-like domain and not at the dimer interface as observed for nuclear transport factor 2. ITC studies showed specificity towards the FxFG motif but not FG and GLFG motifs. The unliganded form of the G3BP1 NTF2-like domain was solved in two crystal forms to resolutions of 1.6 and 3.3 Å in space groups P212121 and P6322 based on two different constructs, residues 1–139 and 11–139, respectively. Crystal packing of the N-terminal residues against a symmetry related molecule in the P212121 crystal form might indicate a novel ligand binding site that, however, remains to be validated. The crystal structures give insight into the nuclear transportation mechanisms of G3BP and provide a basis for future structure based drug design.
A declarative evolution framework for object-oriented design patterns

Object-oriented design patterns and high-level refactorings are popular means of implementing and evolving large object-oriented software systems. Unfortunately, these techniques are inadequately supported at implementation level by current-day software development environments. To alleviate this problem, we propose to use the promising technique of declarative metaprogramming. It offers a tight, yet flexible, symbiosis between a base language and a metalevel declarative reasoning engine. It provides a uniform and language-independent way to specify design patterns and transformations declaratively, to instantiate patterns and generate code for them, and to deal with the evolution of these pattern instances. Providing support for evolution of a software system in terms of the design pattern instances it uses is the main emphasis of this paper.