Miracle-dz/UniFAR-FTUs huggingface dataset:
Trust and Incentives in Principal-Agent Negotiations

The canonical principal-agent problem involves a risk-neutral principal who must use incentives to motivate a risk-averse agent to take a costly, unobservable action that improves the principal’s payoff. The standard solution requires an inefficient shifting of risk to the agent. This article, however, summarizes experimental research that throws doubt on the validity of this conclusion. Experimental subjects were routinely able to achieve efficiency in agent effort levels without inefficient risk-sharing. These experimental outcomes, while anomalous from the standpoint of principal-agency theory, are quite consistent with other experimental data testing notions of trust-based implicit contracting. Such contracting within a hierarchy may allow an outcome preferred, by both principal and agent, to that deemed possible by principal-agency theory. If this is true, then the lessons to be learned from principal-agency theory are all the wrong ones. Concentrating on incentives can crowd out the very qualities in a relationship that make social efficiency possible.
Cerebral Microvascular Obstruction by Fibrin is Associated with Upregulation of PAI-1 Acutely after Onset of Focal Embolic Ischemia in Rats

The mechanisms underlying cerebral microvascular perfusion deficit resulting from occlusion of the middle cerebral artery (MCA) require elucidation. We, therefore, tested the hypothesis that intravascular fibrin deposition in situ directly obstructs cerebral microcirculation and that local changes in type 1 plasminogen activator inhibitor (PAI-1) gene expression contribute to intravascular fibrin deposition after embolic MCA occlusion. Using laser-scanning confocal microscopy (LSCM) in combination with immunofluorescent staining, we simultaneously measured in three dimensions the distribution of microvascular plasma perfusion deficit and fibrin(ogen) immunoreactivity in a rat model of focal cerebral embolic ischemia (n = 12). In addition, using in situhybridization and immunostaining, we analyzed expression of PAI-1 in ischemic brain (n = 13). A significant (p < 0.05) reduction of cerebral microvascular plasma perfusion accompanied a significant (p < 0.05) increase of intravascular and extravascular fibrin deposition in the ischemic lesion. Microvascular plasma perfusion deficit and fibrin deposition expanded concomitantly from the subcortex to the cortex during 1 and 4 hr of embolic MCA occlusion. Three-dimensional analysis revealed that intravascular fibrin deposition directly blocks microvascular plasma perfusion. Vascular plugs contained erythrocytes, polymorphonuclear leukocytes, and platelets enmeshed in fibrin. In situ hybridization demonstrated induction of PAI-1 mRNA in vascular endothelial cells in the ischemic region at 1 hr of ischemia. PAI-1 mRNA significantly increased at 4 hr of ischemia. Immunohistochemical staining showed the same pattern of increased PAI-1 antigen in the endothelial cells. These data demonstrate, for the first time, that progressive intravascular fibrin deposition directly blocks cerebral microvascular plasma perfusion in the ischemic region during acute focal cerebral embolic ischemia, and upregulation of the PAI-1 gene in the ischemic lesion may foster fibrin deposition through suppression of fibrinolysis.
PubMedPortable: A Framework for Supporting the Development of Text Mining Applications

Information extraction from biomedical literature is continuously growing in scope and importance. Many tools exist that perform named entity recognition, e.g. of proteins, chemical compounds, and diseases. Furthermore, several approaches deal with the extraction of relations between identified entities. The BioCreative community supports these developments with yearly open challenges, which led to a standardised XML text annotation format called BioC. PubMed provides access to the largest open biomedical literature repository, but there is no unified way of connecting its data to natural language processing tools. Therefore, an appropriate data environment is needed as a basis to combine different software solutions and to develop customised text mining applications. PubMedPortable builds a relational database and a full text index on PubMed citations. It can be applied either to the complete PubMed data set or an arbitrary subset of downloaded PubMed XML files. The software provides the infrastructure to combine stand-alone applications by exporting different data formats, e.g. BioC. The presented workflows show how to use PubMedPortable to retrieve, store, and analyse a disease-specific data set. The provided use cases are well documented in the PubMedPortable wiki. The open-source software library is small, easy to use, and scalable to the user’s system requirements. It is freely available for Linux on the web at https://github.com/KerstenDoering/PubMedPortable and for other operating systems as a virtual container. The approach was tested extensively and applied successfully in several projects.
Less reused filter: improving l2 cache performance via filtering less reused lines

The L2 cache is commonly managed using LRU policy. For workloads that have a working set larger than L2 cache, LRU behaves poorly, resulting in a great number of less reused lines that are never reused or reused for few times. In this case, the cache performance can be improved through retaining a portion of working set in cache for a period long enough. Previous schemes approach this by bypassing never reused lines. Nevertheless, severely constrained by the number of never reused lines, sometimes they deliver no benefit due to the lack of never reused lines. This paper proposes a new filtering mechanism that filters out the less reused lines rather than just never reused lines. The extended scope of bypassing provides more opportunities to fit the working set into cache. This paper also proposes a Less Reused Filter (LRF), a separate structure that precedes L2 cache, to implement the above mechanism. LRF employs a reuse frequency predictor to accurately identify the less reused lines from incoming lines. Meanwhile, based on our observation that most less reused lines have a short life span, LRF places the filtered lines into a small filter buffer to fully utilize them, avoiding extra misses. Our evaluation, for 24 SPEC 2000 benchmarks, shows that augmenting a 512KB LRU-managed L2 cache with a LRF having 32KB filter buffer reduces the average MPKI by 27.5%, narrowing the gap between LRU and OPT by 74.4%.
An Overview of Corpus-Based Statistics-Oriented (CBSO) Techniques for Natural Language Processing

A Corpus-Based Statistics-Oriented (CBSO) methodology, which is an attempt to avoid the drawbacks of traditional rule-based approaches and purely statistical approaches, is introduced in this paper. Rule-based approaches, with rules induced by human experts, had been the dominant paradigm in the natural language processing community. Such approaches, however, suffer from serious difficulties in knowledge acquisition in terms of cost and consistency. Therefore, it is very difficult for such systems to be scaled-up. Statistical methods, with the capability of automatically acquiring knowledge from corpora, are becoming more and more popular, in part, to amend the shortcomings of rule-based approaches. However, most simple statistical models, which adopt almost nothing from existing linguistic knowledge, often result in a large parameter space and, thus, require an unaffordably large training corpus for even well-justified linguistic phenomena. The corpus-based statistics-oriented (CBSO) approach is a compromise between the two extremes of the spectrum for knowledge acquisition. CBSO approach emphasizes use of well-justified linguistic knowledge in developing the underlying language model and application of statistical optimization techniques on top of high level constructs, such as annotated syntax trees, rather than on surface strings, so that only a training corpus of reasonable size is needed for training and long distance dependency between constituents could be handled. In this paper, corpus-based statistics-oriented techniques are reviewed. General techniques applicable to CBSO approaches are introduced. In particular, we shall address the following important issues: (1) general tasks in developing an NLP system; (2) why CBSO is the preferred choice among different strategies; (3) how to achieve good performance systematically using a CBSO approach, and (4) frequently used CBSO techniques. Several examples are also reviewed.
MM algorithms for generalized Bradley-Terry models

The Bradley-Terry model for paired comparisons is a simple and muchstudied means to describe the probabilities of the possible outcomes when individuals are judged against one another in pairs. Among the many studies of the model in the past 75 years, numerous authors have generalized it in several directions, sometimes providing iterative algorithms for obtaining maximum likelihood estimates for the generalizations. Building on a theory of algorithms known by the initials MM, for minorization-maximization, this paper presents a powerful technique for producing iterative maximum likelihood estimation algorithms for a wide class of generalizations of the Bradley-Terry model. While algorithms for problems of this type have tended to be custom-built in the literature, the techniques in this paper enable their mass production. Simple conditions are stated that guarantee that each algorithm described will produce a sequence that converges to the unique maximum likelihood estimator. Several of the algorithms and convergence results herein are new.
Everything you should know about postpolypectomy electrocoagulation syndrome

Poster: "ECR 2014 / C-2153 / Everything you should know about postpolypectomy electrocoagulation syndrome" by: "M. C. Canete Moslero1, E. Navarro-Sanchis1, S. Claret Loaiza1, M. Villa Perez2, C. de la Torre1, R. Rodriguez Ortega1, M. Molinero Perez1, A. Sanchez Tovar1; 1Malaga/ES, 2TORREMOLINOS/ES"
VIMOS-VLT spectroscopy of the giant Lyα nebulae associated with three z ~ 2.5 radio galaxies

The morphological and spectroscopic properties of the giant (>60 kpc) Lyα nebulae associated with three radio galaxies at z ∼ 2.5 (MRC 1558‐003, 2025‐218 and 0140‐257) have been investigated using integral field spectroscopic data obtained with the Visible Multi-Object Spectrograph (VIMOS) on VLT. The morphologies are varied. The nebula of one source has a centrally peaked, rounded appearance. In the other two objects, it consists of two spatial components. The three nebulae are aligned with the radio axis within � 30 ◦ . The total Lyα luminosities are in the range (0.3‐3.4) × 10 44 erg s −1 . The Lyα spectral profile shows strong variation through the nebulae, with full width at half-maximum (FWHM) values in the range ∼400‐1500 km s −1 and velocity shifts Voffset ∼ 120‐600 km s −1 . We present an infall model that can successfully explain the morphology, size, surface brightness distribution and the velocity field of the Lyα nebula associated with MRC 1558‐ 003. It can also explain why Lyα is redshifted relative to other emission lines and the FWHM values of the non-resonant He II line. This adds further support to our previous conclusion that the quiescent giant nebulae associated with this and other high-redshift powerful radio galaxies are in infall. A problem for this model is the difficulty to reproduce the large Lyα FWHM values, which might be the consequence of a different mechanism. We have discovered a giant (∼85 kpc) Lyα nebula associated with the radio galaxy MRC 0140‐257 at z = 2.64. It shows strikingly relaxed kinematics (FWHM < 300 km s −1 and Voffset � 120 km s −1 ), unique among high-z (� 2) radio galaxies.
Evolution is the Root of All Evil: An Examination of the Paranoid Style of Creation Science Evangelism

This essay argues that Kent Hovind’s Creation Science Evangelism message fits within the paranoid style of rhetoric first developed by Richard Hofstadter. Specifically this article will focus on an examination of rudiments of the paranoid style that were extracted from Hofstadter’s work by Lesley Di Mare and Craig Allen Smith. This analysis will be comprised of the elements that both exemplify the paranoid style and that have developed uniquely to the field of modern creation science. While deliberating components of Hovind’s Creation Science in its entirety, this work will spotlight two artifacts; part four of Hovind’s Creation Science Seminar and Hovind’s “college level course” Creation Science 103.
A methodology for high performance computation of fully inhomogeneous turbulent flows

A large‐eddy simulation methodology for high performance parallel computation of statistically fully inhomogeneous turbulent flows on structured grids is presented. Strategies and algorithms to improve the memory efficiency as well as the parallel performance of the subgrid‐scale model, the factored scheme, and the Poisson solver on shared‐memory parallel platforms are proposed and evaluated. A novel combination of one‐dimensional red–black/line Gauss–Seidel and two‐dimensional red–black/line Gauss–Seidel methods is shown to provide high efficiency and performance for multigrid relaxation of the Poisson equation. Parallel speedups are measured on various shared‐distributed memory systems. Validations of the code are performed in large‐eddy simulations of turbulent flows through a straight channel and a square duct. Results obtained from the present solver employing a Lagrangian dynamic subgrid‐scale model show good agreements with other available data. The capability of the code for more complex flows is assessed by performing a large‐eddy simulation of the tip‐leakage flow in a linear cascade. Copyright © 2006 John Wiley & Sons, Ltd.
The Temporal Lobes Differentiate between the Voices of Famous and Unknown People: An Event-Related fMRI Study on Speaker Recognition

It is widely accepted that the perception of human voices is supported by neural structures located along the superior temporal sulci. However, there is an ongoing discussion to what extent the activations found in fMRI studies are evoked by the vocal features themselves or are the result of phonetic processing. To show that the temporal lobes are indeed engaged in voice processing, short utterances spoken by famous and unknown people were presented to healthy young participants whose task it was to identify the familiar speakers. In two event-related fMRI experiments, the temporal lobes were found to differentiate between familiar and unfamiliar voices such that named voices elicited higher BOLD signal intensities than unfamiliar voices. Yet, the temporal cortices did not only discriminate between familiar and unfamiliar voices. Experiment 2, which required overtly spoken responses and allowed to distinguish between four familiarity grades, revealed that there was a fine-grained differentiation between all of these familiarity levels with higher familiarity being associated with larger BOLD signal amplitudes. Finally, we observed a gradual response change such that the BOLD signal differences between unfamiliar and highly familiar voices increased with the distance of an area from the transverse temporal gyri, especially towards the anterior temporal cortex and the middle temporal gyri. Therefore, the results suggest that (the anterior and non-superior portions of) the temporal lobes participate in voice-specific processing independent from phonetic components also involved in spoken speech material.
Predictive value of thymidylate synthase and dihydropyrimidine dehydrogenase protein expression on survival in adjuvantly treated stage III colon cancer patients.

BACKGROUND The predictive value of thymidylate synthase (TS) and dihydropyrimidine dehydrogenase (DPD) expression on long-term survival by influencing 5-fluorouracil (5-FU) effect were determined in primary tumours and node metastases of stage III colon cancer patients treated adjuvantly with 5-FU regimens (n=391). The effect of TP 53 mutation status, which is thought to be functionally linked to TS inhibition, was also examined. PATIENTS AND METHODS TS and DPD protein expression was determined by immunohistochemical analysis using tissue microarrays of these colon tumours. Two hundred and twenty tumours had already been screened in a previous study for TP 53 mutations. RESULTS Low TS protein levels in primary stage III colon tumours appeared to be associated with mucinous histology and low DPD protein levels with young age at time of randomisation. Concordance between TS and DPD expression in primary and metastatic tumours was low. No associations were found between disease-free survival (DFS) and TS or DPD protein levels. When stratified by TP 53 mutation status DFS did not differ with TS expression. CONCLUSIONS Expression of TS and DPD proteins is not predictive for survival in patients with stage III colon cancer treated adjuvantly with 5-FU regimens. TS protein levels did not alter the effect of TP 53 mutation status.
MIMO-OFDM channel estimation using distributed compressed sensing

This paper proposes a method of sparse channel estimation using compressed sensing for MIMO-OFDM system. The channel estimation is formulated as a sparse recovery problem because of the maximum delay spread in the high data rate OFDM communication systems. The proposed Distributed Compressed Sensing (DCS) algorithm for channel estimation in MIMO-OFDM system exploits the join sparsity of the MIMO channel. It takes less number of iterations in solving the channel estimation problem and runs much faster than the existing Compressive Sampling Matching Pursuit (CoSaMP). Simulation results demonstrate the validity of the algorithm. For the MIMO channels of unknown sparse degrees, the proposed DCS algorithm gives good channel estimation performance with less number of subcarriers reducing the complexity of the system.
Contingency Perception and Agency Measure in Visuo-Motor Spiking Neural Networks

Agency is the sense that I am the cause or author of a movement. Babies develop early this feeling by perceiving the contingency between afferent (sensor) and efferent (motor) information. A comparator model is hypothesized to be associated with many brain regions to monitor and simulate the concordance between self-produced actions and their consequences. In this paper, we propose that the biological mechanism of spike timing-dependent plasticity, that synchronizes the neural dynamics almost everywhere in the central nervous system, constitutes the perfect algorithm to detect contingency in sensorimotor networks. The coherence or the dissonance in the sensorimotor information flow imparts then the agency level. In a head-neck-eyes robot, we replicate three developmental experiments illustrating how particular perceptual experiences can modulate the overall level of agency inside the system; i.e., (1) by adding a delay between proprioceptive and visual feedback information, (2) by facing a mirror, and (3) a person. We show that the system learns to discriminate animated objects (self-image and other persons) from other type of stimuli. This suggests a basic stage representing the self in relation to others from low-level sensorimotor processes. We discuss then the relevance of our findings with neurobiological evidences and development psychological observations for developmental robots.
Improving Relevance Prediction by Addressing Biases and Sparsity in Web Search Click Data

In this paper, we present our approach and findings in participating the 2012 Yandex Relevance Prediction Challenge. Our approach has two goals: on one hand, we aim to address four types of biases, namely, position-bias, perception-bias, query-bias, and session-bias to better interpret the clickthrough information; on the other hand, we aim to address the clickthrough sparsity by exploiting various back-off strategies. We use gradient boosted regression trees to combine the different features and model the interactions among them. Our final submission ranks 3rd (AUC 0.6635) among the prize eligible participants on the first subset of test queries, but drops to 8th (AUC 0.6536) on the second (hidden) subset, which is potentially due to over-fitting. In this paper, we also discuss our post-competition efforts in addressing this issue through crossvalidation and more careful model selection.
Modelling carbon stocks and fluxes in the wood product sector: a comparative review

In addition to forest ecosystems, wood products are carbon pools that can be strategically managed to mitigate climate change. Wood product models (WPMs) simulating the carbon balance of wood production, use and end of life can complement forest growth models to evaluate the mitigation potential of the forest sector as a whole. WPMs can be used to compare scenarios of product use and explore mitigation strategies. A considerable number of WPMs have been developed in the last three decades, but there is no review available analysing their functionality and performance. This study analyses and compares 41 WPMs. One surprising initial result was that we discovered the erroneous implementation of a few concepts and assumptions in some of the models. We further described and compared the models using six model characteristics (bucking allocation, industrial processes, carbon pools, product removal, recycling and substitution effects) and three model‐use characteristics (system boundaries, model initialization and evaluation of results). Using a set of indicators based on the model characteristics, we classified models using a hierarchical clustering technique and differentiated them according to their increasing degrees of complexity and varying levels of user support. For purposes of simulating carbon stock in wood products, models with a simple structure may be sufficient, but to compare climate change mitigation options, complex models are needed. The number of models has increased substantially over the last ten years, introducing more diversity and accuracy. Calculation of substitution effects and recycling has also become more prominent. However, the lack of data is still an important constraint for a more realistic estimation of carbon stocks and fluxes. Therefore, if the sector wants to demonstrate the environmental quality of its products, it should make it a priority to provide reliable life cycle inventory data, particularly regarding aspects of time and location.