Miracle-dz/UniFAR-FTUs huggingface dataset:
The role of self-interest in elite bargaining

Significance Humans frequently act contrary to their self-interest and reject low offers in bargaining games. Some evidence suggests that elites, however, are much more rational and self-interested, but this hypothesis has never been directly tested in bargaining games. Using a unique sample of US policy and business elites, we find the opposite. Compared with typical convenience samples, elites are even more prone to act contrary to self-interest by rejecting low offers when bargaining. Appearing to anticipate this fact, elites also make higher offers. This may help to explain why policy elites, such as the diplomats who negotiate treaties on topics like global warming, pay close attention to distributional concerns even though such concerns have been a perennial source of policy gridlock. One of the best-known and most replicated laboratory results in behavioral economics is that bargainers frequently reject low offers, even when it harms their material self-interest. This finding could have important implications for international negotiations on many problems facing humanity today, because models of international bargaining assume exactly the opposite: that policy makers are rational and self-interested. However, it is unknown whether elites who engage in diplomatic bargaining will similarly reject low offers because past research has been based almost exclusively on convenience samples of undergraduates, members of the general public, or small-scale societies rather than highly experienced elites who design and bargain over policy. Using a unique sample of 102 policy and business elites who have an average of 21 y of practical experience conducting international diplomacy or policy strategy, we show that, compared with undergraduates and the general public, elites are actually more likely to reject low offers when playing a standard “ultimatum game” that assesses how players bargain over a fixed resource. Elites with more experience tend to make even higher demands, suggesting that this tendency only increases as policy makers advance to leadership positions. This result contradicts assumptions of rational self-interested behavior that are standard in models of international bargaining, and it suggests that the adoption of global agreements on international trade, climate change, and other important problems will not depend solely on the interests of individual countries, but also on whether these accords are seen as equitable to all member states.
On the Deep Order-Preserving Submatrix Problem: A Best Effort Approach

Order-preserving submatrix (OPSM) has been widely accepted as a biologically meaningful cluster model, capturing the general tendency of gene expression across a subset of experiments. In an OPSM, the expression levels of all genes induce the same linear ordering of the experiments. The OPSM problem is to discover those statistically significant OPSMs from a given data matrix. The problem is reducible to a special case of the sequential pattern mining problem, where a pattern and its supporting sequences uniquely specify an OPSM. Unfortunately, existing methods do not scale well to massive data sets containing thousands of experiments and hundreds of thousands of genes, which are common in today's gene expression analysis. In particular, deep OPSMs, corresponding to long patterns with few supporting sequences, incur explosive computational costs in their discovery and are completely pruned off by existing methods. However, it is of particular interest of biologists to determine small groups of genes that are tightly coregulated across many experiments, and some pathways or processes may require as few as two genes to act in concert. In this paper, we study the discovery of deep OPSMs from massive data sets. We propose a novel best effort mining framework Kiwi that exploits two parameters k and w to bound the available computational resources and search a selected search space, and does what it can to find as many as possible deep OPSMs. Extensive biological and computational evaluations on real data sets demonstrate the validity and importance of the deep OPSM problem, and the efficiency and effectiveness of the Kiwi mining framework.
EXIT Chart Based Design of Irregular LDPC Codes for Large-MIMO Systems

In this letter, we characterize the extrinsic information transfer (EXIT) behavior of a factor graph based message passing algorithm for detection in large multiple-input multiple-output (MIMO) systems with tens to hundreds of antennas. The EXIT curves of a joint detection-decoding receiver are obtained for low density parity check (LDPC) codes of given degree distributions. From the obtained EXIT curves, an optimization of the LDPC code degree profiles is carried out to design irregular LDPC codes matched to the large-MIMO channel and joint message passing receiver. With low complexity joint detection-decoding, these codes are shown to perform better than off-the-shelf irregular codes in the literature by about 1 to 1.5 dB at a coded BER of 10-5 in 16 × 16, 64 × 64 and 256 × 256 MIMO systems.
Sharing of Images in Content Sharing Sites Based On User Profile Inferences

Usage of social media are increased considerably in today world it enables the user to share images with one another. Sharing the images may leads to performance violation. Web mining is use of data mining technique to discover and extract the information from the web. Web content mining is the extraction and integration of data, information and knowledge from web page. In the web, one can mine the images and find association between various images. Privacy techniques needed to adapt in order to improve the satisfaction level of user, by means of automated privacy policy generation. Adaptive Privacy Policy Prediction system helps the user to compose customized privacy settings. A Two level framework is proposed with Speeded Up Robust Feature for identifying the feature points of an images, by demonstrating in MATLAB tool. The region of selected points is an effective method for identifying the extracted features in the images based on the image feature extraction.
How generation intervals shape the relationship between growth rates and reproductive numbers

Mathematical models of transmission have become invaluable management tools in planning for the control of emerging infectious diseases. A key variable in such models is the reproductive number R. For new emerging infectious diseases, the value of the reproductive number can only be inferred indirectly from the observed exponential epidemic growth rate r. Such inference is ambiguous as several different equations exist that relate the reproductive number to the growth rate, and it is unclear which of these equations might apply to a new infection. Here, we show that these different equations differ only with respect to their assumed shape of the generation interval distribution. Therefore, the shape of the generation interval distribution determines which equation is appropriate for inferring the reproductive number from the observed growth rate. We show that by assuming all generation intervals to be equal to the mean, we obtain an upper bound to the range of possible values that the reproductive number may attain for a given growth rate. Furthermore, we show that by taking the generation interval distribution equal to the observed distribution, it is possible to obtain an empirical estimate of the reproductive number.
The ergonomics of computer interfaces -- Designing a system for human use.

This document discusses the ergonomic problems with currently available software products, and what in general is necessary in order to make an application pleasant to work with. The application of these principles to a new open-architecture user interface system, Views, is then described. 1991 Mathematics Subject Classification: 68U99. 1991 CR Categories: H.1. 2, H.5. 2, D39, H.5. 0, I.7. 2.
Parallax: Managing Storage for a Million Machines

OS virtualization is drastically changing the face of system administration for large computer installations such as commercial datacenters and scientific clusters. A recent report by Gartner predicts that commercial use of virtualization will triple over the five year period beginning in 2004 [1]. While it is commonly held that OS virtualization improves the utility, manageability, and scalability of large-scale environments, we believe that it is not sufficient in itself. In this paper we argue that the next key challenge facing these environments lies in the dramatically evolving requirements for the management of persistent storage.
Emergent search on double circle TSPs using subgour exchange crossover

Genetic algorithms (GAs) have such potentials for realizing emergent searches that local search techniques, such as simulated annealings, and parallel local search techniques, like other evolutionary computation such as evolution strategies and evolutionary programmings, do not have. Crossover operators bring these potentials because they can emerge their neighborhood structures as populations evolve. The paper presents a realization of emergent searches by GAs. First, we show difficulties for local search techniques to solve double circle TSPs, and discuss how emergent searches can overcome such difficulties. Second, we propose guidelines to achieve emergent searches by GAs; the characteristics preserving encodings/crossovers design and the diversity maintaining generation alternation models design. According to these guidelines, we actually realize GAs to solve double circle TSPs.
Effect of inhibition of the lysophosphatidic acid receptor 1 on metastasis and metastatic dormancy in breast cancer.

BACKGROUND Previous studies identified the human nonmetastatic gene 23 (NME1, hereafter Nm23-H1) as the first metastasis suppressor gene. An inverse relationship between Nm23-H1 and expression of lysophosphatidic acid receptor 1 gene (LPAR1, also known as EDG2 or hereafter LPA1) has also been reported. However, the effects of LPA1 inhibition on primary tumor size, metastasis, and metastatic dormancy have not been investigated. METHODS The LPA1 inhibitor Debio-0719 or LPA1 short hairpinned RNA (shRNA) was used. Primary tumor size and metastasis were investigated using the 4T1 spontaneous metastasis mouse model and the MDA-MB-231T experimental metastasis mouse model (n = 13 mice per group). Proliferation and p38 intracellular signaling in tumors and cell lines were determined by immunohistochemistry and western blot to investigate the effects of LPA1 inhibition on metastatic dormancy. An analysis of variance-based two-tailed t test was used to determine a statistically significant difference between treatment groups. RESULTS In the 4T1 spontaneous metastasis mouse model, Debio-0719 inhibited the metastasis of 4T1 cells to the liver (mean = 25.2 liver metastases per histologic section for vehicle-treated mice vs 6.8 for Debio-0719-treated mice, 73.0% reduction, P < .001) and lungs (mean = 6.37 lesions per histologic section for vehicle-treated mice vs 0.73 for Debio-0719-treated mice, 88.5% reduction, P < .001), with no effect on primary tumor size. Similar results were observed using the MDA-MB-231T experimental pulmonary metastasis mouse model. LPA1 shRNA also inhibited metastasis but did not affect primary tumor size. In 4T1 metastases, but not primary tumors, expression of the proliferative markers Ki67 and pErk was reduced by Debio-0719, and phosphorylation of the p38 stress kinase was increased, indicative of metastatic dormancy. CONCLUSION The data identify Debio-0719 as a drug candidate with metastasis suppressor activity, inducing dormancy at secondary tumor sites.
Multi-Hypergraph Consistent Sparse Coding

Sparse representation has been a powerful technique for modeling high-dimensional data. As an unsupervised technique to extract sparse representations, sparse coding encodes the original data into a new sparse code space and simultaneously learns a dictionary representing high-level semantics. Existing methods have considered local manifold within high-dimensional data using graph/hypergraph Laplacian regularization, and more from the manifold could be utilized to improve the performance. In this article, we propose to further regulate the sparse coding so that the learned sparse codes can well reconstruct the hypergraph structure. In particular, we add a novel hypergraph consistency regularization term (HC) by minimizing the reconstruction error of the hypergraph incidence or weight matrix. Moreover, we extend the HC term to multi-hypergraph consistent sparse coding (MultiCSC) and automatically select the optimal manifold structure under the multi-hypergraph learning framework. We show that the optimization of MultiCSC can be solved efficiently, and that several existing sparse coding methods can fit into the general framework of MultiCSC as special cases. As a case study, hypergraph incidence consistent sparse coding is applied to perform semi-auto image tagging, demonstrating the effectiveness of hypergraph consistency regulation. We perform further experiments using MultiCSC for image clustering, which outperforms a number of baselines.
On the k-Atomicity-Verification Problem

Modern Internet-scale storage systems often provide weak consistency in exchange for better performance and resilience. An important weak consistency property is k-atomicity, which bounds the staleness of values returned by read operations. The k-atomicity-verification problem (or k-AV for short) is the problem of deciding whether a given history of operations is k-atomic. The 1-AV problem is equivalent to verifying atomicity/linearizability, a well-known and solved problem. However, for k ≥ 2, no polynomial-time k-AV algorithm is known. This paper makes the following contributions towards solving the k-AV problem. First, we present a simple 2-AV algorithm called LBT, which is likely to be efficient (quasilinear) for histories that arise in practice, although it is less efficient (quadratic) in the worst case. Second, we present a more involved 2-AV algorithm called FZF, which runs efficiently (quasilinear) even in the worst case. To our knowledge, these are the first algorithms that solve the 2-AV problem fully. Third, we show that the weighted k-AV problem, a natural extension of the k-AV problem, is NP-complete.
When is a union really an intersection? Problems interpreting reference to locations in a dialogue system

This paper describes issues that arose in our implementation of an interpreter for locative expressions in a spoken dialogue system. The expressions involve complex adverbial modification, include imprecise and innacurate content, and reflect conventional practices specific to the way English speakers refer to roads and highways. Our system utilizes semantic features in the parser to perform disambiguation, and domain-specific reasoning to resolve variables in the logical form to the correct referent. The functionality implemented to date was evaluated against a small corpus of naturally-produced expressions, of which 46% were correctly interpreted.
Hardware-Accelerated Lagrangian-Eulerian Texture Advection for 2D Flow Visualization

A hardware-based approach for visualizing unsteady flow fields by means of Lagrangian-Eulerian advection is presented. Both noise-based and dyebased texture advection is supported. The implementation allows the advection of each texture to be performed completely on the graphics hardware in a single-pass rendering. We discuss experiences with the interactive visualization of unsteady flow fields that become possible due to the high visualization speed of the hardware-based approach.
Partial fingerprint matching based on SIFT Features

— Fingerprints are being extensively used for person identification in a number of commercial, civil, and forensic applications. The current Fingerprint matching technology is quite mature for matching full prints, matching partial fingerprints still needs lots of improvement. Most of the current fingerprint identification systems utilize features that are based on minutiae points and ridge patterns. The major challenges faced in partial fingerprint matching are the absence of sufficient minutiae features and other structures such as core and delta. However, this technology suffers from the problem of handling incomplete prints and often discards any partial fingerprints obtained. Recent research has begun to delve into the problems of latent or partial fingerprints. In this paper we present a novel approach for partial fingerprint matching scheme based on SIFT (Scale Invariant Feature Transform) features and matching is achieved using a modified point matching process. Using Neurotechnology database, we demonstrate that the proposed method exhibits an improved performance when matching full print against partial print
Parsimonious Naive Bayes

We describe our submission to the AAIA'14 Data Mining Competition, where the objective was to reach good predictive performance on text mining classification problems while using a small number of variables. Our submission was ranked 6th, less than 1% behind the winner. We also present an empirical study on the trade-off between parsimony of the representation and accuracy, and show how good performance can be obtained quickly and efficiently.
Aortic valve perforation following transcoronary ablation of septal hypertrophy

We report the case of a 47-year-old man with hypertrophic obstructive cardiomyopathy who underwent transcoronary ablation of septal hypertrophy and developed severe aortic regurgitation after the procedure. Intra-operatively, we found a wide perforation of the noncoronary cusp, and performed aortic valve replacement.
Evaluation as a service for information retrieval

How can we run large-scale, community-wide evaluations of information retrieval systems if we lack the ability to distribute the document collection on which the task is based? This was the challenge we faced in the TREC Microblog tracks over the past few years. In this paper, we present a novel evaluation methodology we dub "evaluation as a service", which was implemented at TREC 2013 to address restrictions on data redistribution. The basic idea is that instead of distributing the document collection, we (the track organizers) provided a service API "in the cloud" with which participants could accomplish the evaluation task. We outline advantages as well as disadvantages of this evaluation methodology, and discuss how the approach might be extended to other evaluation scenarios.
Bone Damage in Autoimmune Arthritis Potently Accelerates Osteoclast-Mediated

We have recently proposed that the shared epitope (SE) may contribute to rheumatoid arthritis pathogenesis by acting as a ligand that activates proarthritogenic signal transduction events. To examine this hypothesis, in this study we characterized a novel small SE-mimetic compound, c (HS4-4), containing the SE primary sequence motif QKRAA, which was synthesized using a backbone cyclization method. The SE-mimetic c (HS4-4) compound interacted strongly with the SE receptor calreticulin, potently activated NO and reactive oxygen species production, and markedly facilitated osteoclast differentiation and function in vitro. The pro-osteoclastogenic potency of c (HS4-4) was 100,000- to 1,000,000-fold higher than the potency of a recently described linear SE peptidic ligand. When administered in vivo at nanogram doses, c (HS4-4) enhanced Th17 expansion, and in mice with collagen-induced arthritis it facilitated disease onset, increased disease incidence and severity, enhanced osteoclast abundance in synovial tissues and osteoclastogenic propensities of bone marrow–derived cells, and augmented bone destruction. In conclusion, c (HS4-4), a highly potent small SE-mimetic compound enhances bone damage and disease severity in inﬂammatory arthritis. These ﬁndings support the hypothesis that the SE acts as a signal transduction ligand that activates a CRT-mediated proarthritogenic pathway. The Journal of Immunology , 2013, 191: 000–000. FINDSITE (23)] and ab initio method ConCavity (24). In the template-based approaches, sequence proﬁle and structural comparisons are used to recognize the tem- plate proteins from the known function library BioLip (21), from which the ligand-binding information of the target is transferred; in the ab initio approach, the ligand binding site is derived from the cavity distribution on the surface of the target structures. A consensus binding pocket in the receptor structure was predicted by COACH, which is tethered by residues 216–225 and 255–260. The c (HS4-4) ligand was then docked onto the predicted binding pocket, using the ligand-docking software DOCK6 (25).
Critical Role of β3 Integrin in Experimental Postmenopausal Osteoporosis

We show that mice lacking β3 integrin are protected from OVX‐induced bone loss. Using a lentiviral‐based strategy to express β3 mutants in β3−/− mice, we also show that β3S752, but not β3Y747/Y759, is important for osteoclastic bone resorption in vivo.
Tour of a Labyrinth: Exploring the Vertebrate Nose

This special issue of The Anatomical Record is the outcome of a symposium entitled “Inside the Vertebrate Nose: Evolution, Structure and Function. ” The skeletal framework of the nasal cavity is a complicated structure that often houses sinuses and comprises an internal skeleton of bone or cartilage that can vary greatly in architecture among species. The nose serves multiple functions, including olfaction and respiratory air‐conditioning, and its morphology is constrained by evolution, development, and conflicting demands on cranial space, such as enlarged orbits. The nasal cavity of vertebrates has received much more attention in the last decade due to the emergence of nondestructive methods that allow improved visualization of the internal anatomy of the skull, such as high‐resolution x‐ray computed tomography and magnetic resonance imaging. The 17 articles included here represent a broad range of investigators, from paleontologists to engineers, who approach the nose from different perspectives. Key topics include the evolution and development of the nose, its comparative anatomy and function, and airflow through the nasal cavity of individual species. In addition, this special issue includes review articles on anatomical reduction of the olfactory apparatus in both cetaceans and primates (the vomeronasal system), as well as the molecular biology of olfaction in vertebrates. Together these articles provide an expansive summary of our current understanding of vertebrate nasal anatomy and function. In this introduction, we provide background information and an overview of each of the three primary topics, and place each article within the context of previous research and the major challenges that lie ahead. Anat Rec, 297:1975–1984, 2014. © 2014 Wiley Periodicals, Inc.