Miracle-dz/UniFAR-FTUs huggingface dataset:
An Experimental Test of Equilibrium Dominance in Signaling Games

Many economic situations with asymmetric information can be modeled as signaling games. Even simple signaling games can have sequential equilibria that are considered "unintuitive. " For example, in a wellknown model due to Michael Spence (1973), workers with good information about their own ability levels have to decide whether to obtain additional education or not. An employer, knowing that education is more costly for low-ability workers, observes the education signal, but not the worker's ability, prior to deciding on a wage offer. As shown below, it is possible to construct examples in which all types of workers decide against the educational investment because the employer will interpret education as a signal of low ability, even though the signal is not less costly for low-ability workers. Despite the unintuitive nature of these "out-of-equilibrium beliefs," this equilibrium outcome survives the tests imposed by all of the commonly used, strengthened versions of the Nash concept. In particular, this outcome is a sequential equilibrium in the sense of David M. Kreps and Robert Wilson (1982); it satisfies a backwards-induction rationality requirement that decisions be optimal from any nonterminal stage until the end of the game, given the equilibrium beliefs at that stage. Despite the fact that unintuitive outcomes can pass the test imposed by a sequential equilibrium, there is no consensus on exactly how this equilibrium concept should be strengthened or "refined. " The recent debate centers on refinements that place more restrictions on players' beliefs about what would happen off the equilibrium path. Several refinements have been proposed, each of which is motivated by specific games in which a weaker refinement permits unreasonable equilibria. For example, In-Koo Cho and Kreps (1987) discuss their "intuitive criterion," which is based on a dominance notion that they call equilibrium dominance. They also discuss a number of stronger refinements, including strategic stability (Elon Kohlberg and JeanFrancois Mertens, 1986) and divinity (Jeffrey Banks and Joel Sobel, 1987). 1 We are particularly interested in equilibrium dominance, since it is widely discussed and since it is implied by stronger refinements. The arguments about which refinement is appropriate are typically based on subjective opinions about how reasonable individuals would behave. There is an apparent need for empirical work that directly tests the validity of these arguments; such work could guide the theoretical debate toward alternative refinements. Although game theory is sometimes used as a normative theory about how "rational" agents ought to behave, the theory is also widely applied in
Evidence of Self-Sustaining Drug Resistant HIV-1 Lineages Among Untreated Patients in the United Kingdom.

BACKGROUND About 10% of new diagnoses of subtype B human immunodeficiency virus type 1 (HIV-1) in the United Kingdom are with viruses showing transmitted drug resistance (TDR). However, there is discordance between the mutation patterns observed in HIV-infected patients failing therapy and those seen in TDR. METHODS We extracted all subtype B HIV-1 pol gene sequences from treatment-naive patients within the United Kingdom HIV Drug Resistance Database sampled between 1997 and 2011 and carrying the most common protease inhibitors, nonnucleoside and nucleotide reverse transcriptase inhibitors TDR mutations, namely, L90M, K103N, and T215Y/F/rev, respectively (n = 1140). Transmission clusters (n ≥ 2 sequences) were identified by maximum-likelihood phylogeny using a genetic distance cutoff of ≤ 1.5%. The time of origin and the basic reproductive number (R0) of clusters were estimated by Bayesian methods. RESULTS T215rev was present alone in 47% of the sequences (n = 540), K103N in 31% (n = 359), and L90M in 10% (n = 109). The remaining sequences contained T215Y or combinations of L90M, K103N, and T215rev. Fifty-five percent (n = 624) of the sequences formed highly supported transmission clusters (n = 193) containing between 2 and 15 sequences. The time of origin of 10 large clusters (≥ 8 sequences) was estimated to be between 2000 (1999-2002; 95% highest posterior density [HPD]) and 2006 (2005-2007; 95% HPD). The oldest cluster had persisted for nearly 8 years. All 10 clusters had R0s ranging from 1.3 (0.4-2.5; 95% HPD) to 2.8 (0.6-6.5; 95% HPD). CONCLUSIONS A high proportion of the most common TDR in subtype B infections in the United Kingdom is derived by onward transmission from treatment-naive patients.
Extension Information-Knowledge-Strategy System for Semantic Interoperability

This paper discusses the issue of information interoperability. In view of the problems that it is difficult to solve the semantic conflicts in information interoperability, the paper shows how to build the extension ontology model for information interoperability based on Extenics information- knowledge-Strategy system. Take advantage of Extenics’ feature of contradiction problem solving, the extension system can eliminate semantic conflicts by extension transformation method. It overcomes the drawbacks of current ontology models that lacks transformation mechanisms, therefore supports information interoperability effectively. The paper presents examples of semantic interoperability process with the extension system. It describes some implement technologies of the extension system.
Multifocus image fusion using Discrete Wavelet Transform and Sparse Representation

Multifocus image fusion increases the depth of field of a sensor by combining the images of same scene with different focus settings. So, extracting the useful image information of different source images plays a crucial role in image fusion process. In this paper, a novel fusion algorithm based on Discrete Wavelet Transform (DWT) and Sparse Representation (SR) is proposed. Initially, DWT is applied to extract the low frequency components and high frequency components of source images. High frequency components are merged using SR based fusion approach and low frequency components are combined using variance as activity level measurement. Finally, inverse DWT is performed on the fused coefficients to get the fused image. Experimental results demonstrate the effectiveness of proposed method in terms of visual perception and quantitative analysis.
Building a scalable and accurate copy detection mechanism

Often, publishers are reluctant to offer valuable digital documentson the Internet for fear that they will be re-transmitted or copiedwidely. A Copy Detection Mechanism can help identify such copying.For example, publishers may register their documents with a copydetection server, and the server can then automatically checkpublic sources such as UseNet articles and Web sites for potentialillegal copies. The server can search for exact copies, and alsofor cases where significant portions of documents have been copied.In this paper we study, for the first time, the performance ofvarious copy detection mechanisms, including the disk storagerequirements, main memory requirements, response times forregistration, and response time for querying. We also contrastperformance to the accuracy of the mechanisms (how well they detectpartial copies). The results are obtained using SCAM, anexperimental server we have implemented, and a collection of 50,000netnews articles.
Combined Pharmacotherapy for the Treatment of Traumatic Brain Injury Rehabilitation and Recovery of Function Following Prefrontal Cortex Controlled Cortical Impact in Rats

Traumatic brain injury (TBI) is common among military personnel, resulting from bomb blasts and explosions. The secretion of pro-inflammatory cytokines following TBI has been linked to cerebral edema and neuronal loss. The use of lovastatin for TBI has been suggested to be neuroprotective by combating cytokines and inflammation. Fluoxetine has been suggested to aid in the prevention of edema during secondary injury processes, as well as having a relationship to neural plasticity. Seventy-six Long-Evans rats were randomly assigned to CCI (controlled cortical impact) or sham-operated as well as one of the following drug conditions: no treatment, vehicle, Fluoxetine only, Lovastatin only, and combined Fluoxetine-Lovastatin. Two behavioral tasks testing motor control and somatosensory input were used to investigate recovery of function. Brain tissue was analyzed using cresyl violet stain and GFAP label. Behavioral and cell count data did not reveal significant improvements between combined Fluoxetine-Lovastatin pharmacotherapy groups and all other groups. Several methodological limitations that may account for these negative findings are discussed. Although the combination of Lovastatin and Fluoxetine did not significantly improve behavioral scores or cell counts
Wall following to escape local minima for swarms of agents using internal states and emergent behaviour

Natural examples of emergent behaviour, in groups due to interactions among the group's individuals, are numerous. Our aim, in this paper, is to use complex emergent behaviour among agents that interact via pair-wise attractive and repulsive potentials, to solve the local minima problem in the artificial potential based navigation method. We present a modified potential field based path planning algorithm, which uses agent internal states and swarm emergent behaviour to enhance group performance. The algorithm is used successfully to solve a reactive path-planning problem that cannot be solved using conventional static potential fields due to local minima formation. Simulation results demonstrate the ability of a swarm of agents to perform problem solving using the dynamic internal states of the agents along with emergent behaviour of the entire group.
Benchmarking Traversal Operations over Graph Databases

A significant number of graph database systems has emerged in the past few years. Most aim at the management of the property graph data structure: where graph elements can be assigned with properties. In this paper, we address the need to compare the performance of different graph databases, and discuss the challenges of developing fair benchmarking methodologies. We believe that, compared to other database systems, the ability to efficiently traverse over the graph topology is unique to graph databases. As such, we focus our attention on the benchmarking of traversal operations. We describe the design of the graph traversal benchmark and present its results. The benchmark provides the means to compare the performance of different data management systems and gives us insight into the abilities and limitations of modern graph databases.
A Game Theory Algorithm for Intra-Cluster Data Aggregation in a Vehicular Ad Hoc Network

Vehicular ad hoc networks (VANETs) have an important role in urban management and planning. The effective integration of vehicle information in VANETs is critical to traffic analysis, large-scale vehicle route planning and intelligent transportation scheduling. However, given the limitations in the precision of the output information of a single sensor and the difficulty of information sharing among various sensors in a highly dynamic VANET, effectively performing data aggregation in VANETs remains a challenge. Moreover, current studies have mainly focused on data aggregation in large-scale environments but have rarely discussed the issue of intra-cluster data aggregation in VANETs. In this study, we propose a multi-player game theory algorithm for intra-cluster data aggregation in VANETs by analyzing the competitive and cooperative relationships among sensor nodes. Several sensor-centric metrics are proposed to measure the data redundancy and stability of a cluster. We then study the utility function to achieve efficient intra-cluster data aggregation by considering both data redundancy and cluster stability. In particular, we prove the existence of a unique Nash equilibrium in the game model, and conduct extensive experiments to validate the proposed algorithm. Results demonstrate that the proposed algorithm has advantages over typical data aggregation algorithms in both accuracy and efficiency.
Nonrigid 3D Medical Image Registration and Fusion Based on Deformable Models

For coregistration of medical images, rigid methods often fail to provide enough freedom, while reliable elastic methods are available clinically for special applications only. The number of degrees of freedom of elastic models must be reduced for use in the clinical setting to archive a reliable result. We propose a novel geometry-based method of nonrigid 3D medical image registration and fusion. The proposed method uses a 3D surface-based deformable model as guidance. In our twofold approach, the deformable mesh from one of the images is first applied to the boundary of the object to be registered. Thereafter, the non-rigid volume deformation vector field needed for registration and fusion inside of the region of interest (ROI) described by the active surface is inferred from the displacement of the surface mesh points. The method was validated using clinical images of a quasirigid organ (kidney) and of an elastic organ (liver). The reduction in standard deviation of the image intensity difference between reference image and model was used as a measure of performance. Landmarks placed at vessel bifurcations in the liver were used as a gold standard for evaluating registration results for the elastic liver. Our registration method was compared with affine registration using mutual information applied to the quasi-rigid kidney. The new method achieved 15.11% better quality with a high confidence level of 99% for rigid registration. However, when applied to the quasi-elastic liver, the method has an averaged landmark dislocation of 4.32 mm. In contrast, affine registration of extracted livers yields a significantly (P = 0.000001) smaller dislocation of 3.26 mm. In conclusion, our validation shows that the novel approach is applicable in cases where internal deformation is not crucial, but it has limitations in cases where internal displacement must also be taken into account.
Detection of video double encoding with GOP size estimation

Video forensics is an emerging discipline, that aims at inferring information about the processing history undergone by a digital video in a blind fashion. In this work we introduce a new forensic footprint and, based on it, propose a method for detecting whether a video has been encoded twice; if this is the case, we also estimate the size of the Group Of Pictures (GOP) employed during the first encoding. As shown in the experiments, the footprint proves to be very robust even in realistic settings (i.e., when encoding is carried out using typical compression rates), that are rarely addressed by existing techniques.
The time course of age-related emotional preference in task-irrelevant affective processing

Studies of the age-related positivity effect have demonstrated that older adults have a generalized preference to positive stimuli or avoidance to negative stimuli compared with younger adults. However, it remains unclear when and how this positive effect occurs in task-irrelevant affective processing in the aging brain. The present study investigated age-related emotional preference in one task-irrelevant affective stimuli processing by event-related brain potentials (ERPs) measurement with a specific focus on the time course of older adults' emotional processing and regulation. Younger and older adults completed a modified oddball task in which the deviant stimuli were affective faces. In the relatively early time window, the brain activities were not modulated by emotional valence in younger adults, yet the sad stimuli elicited a larger P3a than the happy and neutral ones in older adults. In the late time window, the sad stimuli elicited a larger positive slow wave than the happy stimuli in younger adults. Contrarily, at the later processing stage older adults' valence differences were eliminated. In general, we found time course differences in how older adults processed task-irrelevant affective stimuli compared, with the young, and an age-related positivity effect occurred in the late time window, manifested as a negativity preference in younger and no preferences in older adults. These results provided evidence for supporting socioemotional selectivity theory from an ERP approach.
Wind Potential determination in a known area

The economic operation of wind turbines is completely dependent upon the local wind conditions. Statistically determined wind velocity distribution is decisive for the expected energy yield. Before the pillars of wind turbines are erected, the expected energy potential should be predicted as precisely as possible to reduce the investments risk. Energy predictions based on local wind conditions measured at the hub height of a planned turbine give the most exactly predictions. However, this involves an expansive and time (years) consuming process. Our issue for fine wind emplacement is based on a Patent Application that claims that the wind potential in any other point of a known area can be inferred provided that we know the wind potential in one point of the area. Our aim is 1) to avoid the obsolete, expansive and inaccurate method to build wind map, and 2) to offer a final simply to be used tool. To solve that problem we must enter in the field of high mathematics of fluid dynamics.
ENERGY SAVING IN WIRELESS SENSOR NETWORK USING OPTIMAL SELECTIVE FORWARDING PROTOCOL

Energy consumption is a primary anxiety in Wireless Sensor Network (WSN). Sensor node batteries cannot be easily refilled and nodes have a finite lifetime. One of the major issues in wireless sensor networks is developing an energyefficient routing protocol to improve the overall lifetime of the network. Several routing protocols are used in WSN for transforming the messages. In epidemic routing the messages are blindly stored and forwarded to all neighboring nodes. This may contain packet loss and energy consumption. To avoid the packet loss and to reduce energy consumption the Dynamic Source Routing (DSR) algorithm with optimal selective forwarding protocol is used. The DSR protocol is a simple and efficient routing protocol. DSR is specifically designed for Wireless sensor Network. In DSR each node (sensors) maintains a routing table. If the route is available in the table the optimal selective forwarding protocol schemes are applied. And also the forwarding schemes are designed for three different cases to improve the lifetime of sensor node batteries such as when Sensors give maximum importance for their own transmitted messages, Sensors give maximum importance for messages that arrive at sink successfully and Sensors give maximum importance for retransmitted messages to one of its neighbors.
Direction finding in correlated noise fields based on joint block-diagonalization of spatio-temporal correlation matrices

Direction of arrival (DOA) estimation techniques require knowledge of the sensor-to-sensor correlation of the noise, which constitutes a significant drawback. In the case of temporally correlated signals, it is possible to estimate the signal parameters without any assumptions made on the spatial covariance matrix of the noise. A new method for the estimation of the signal subspace and noise subspace is introduced. The proposed approach is based on a joint block-diagonalization (JBD) of a combined set of spatio-temporal correlation matrices. Once the signal and the noise subspaces are estimated, any subspace based approach can be applied for DOA estimation. A performance comparison of the proposed approach with an existing technique is provided.
HLA-DRB1 and HLA-DQB1 Are Associated with Adult-Onset Immunodeficiency with Acquired Anti-Interferon-Gamma Autoantibodies

Recently a newly identified clinical syndrome of disseminated non-tuberculous mycobacterial diseases (with or without other opportunistic infections in adult patients who were previously healthy, has been recognized in association with an acquired autoantibody to interferon-gamma. This syndrome is emerging as an important cause of morbidity and mortality, especially among people of Asian descent. Trigger for the production of this autoantibody remains unknown, but genetic factors are strongly suspected to be involved. We compared HLA genotyping between 32 patients with this clinical syndrome, and 38 controls. We found that this clinical syndrome was associated with very limited allele polymorphism, with HLA-DRB1 and DQB1 alleles, especially HLA-DRB1*15:01, DRB1*16:02, DQB1*05:01 and DQB1*05:02. Odds ratio of DRB1*15:01, DRB1*16:02, DQB1*05:01 and DQB1*05:02 were 7.03 (95% CI, 2.18–22.69, P<0.0001, 9.06 (95% CI, 2.79–29.46, P<0.0001), 6.68 (95% CI, 2.29–19.52, P = 0.0004), and 6.64 (95% CI, 2.30–19.20, P = 0.0004), respectively. Further investigation is warranted to provide better understanding on pathogenesis of this association.
Bmc Developmental Biology Identification and Targeted Disruption of the Mouse Gene Encoding Esg1 (ph34/ecat2/dppa5)

Background: Embryonic stem cell-specific gene (ESG) 1, which encodes a KH-domain containing protein, is specifically expressed in early embryos, germ cells, and embryonic stem (ES) cells. Previous studies identified genomic clones containing the mouse ESG1 gene and five pseudogenes. However, their chromosomal localizations or physiological functions have not been determined.
Least-squares performance of analog product codes

In this article the least squares method is utilized for the decoding of analog product codes. In particular it is shown, (i) how the LS solution is constructed for arbitrary image block sizes, (ii) that the theoretical achievable SNR improvement after LS decoding is inverse proportional to the code rate, and finally (iii) the LS results are compared with a known iterative method. The convergence of the iterative method is analyzed, allowing for optimal behavior and a consistent proof of convergence is provided. Theoretical results are compared to simulations on the example of a picture transmission.
Eliminating Public Knowledge Biases in Information-Aggregation Mechanisms

We present a novel methodology for identifying public knowledge and eliminating the biases it creates when aggregating information in small group settings. A two-stage mechanism consisting of an information market and a coordination game is used to reveal and adjust for individuals' public information. A nonlinear aggregation of their decisions then allows for the calculation of the probability of the future outcome of an uncertain event, which can then be compared to both the objective probability of its occurrence and the performance of the market as a whole. Experiments show that this nonlinear aggregation mechanism outperforms both the imperfect market and the best of the participants.