Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterising simple negotiation as distributed agent-based theorem-proving-a preliminary report

Negotiation is a key technique for dynamically organising activity in multi-agent systems, yet the negotiation process itself can often be difficult to reason about. We introduce a framework in which negotiation can be characterised as a form of distributed, multi-agent theorem-proving. Thus, in this preliminary analysis, we show that certain simple forms of negotiation will be successful if, and only if a corresponding theorem can be proved by agents acting as theorem-proving components. We extend this approach further to represent situations where the agent has a choice of possible responses, given a proposal received. In such cases, an ordering strategy is used to select the order in which replies are provided; this corresponds to a common use of ordering within classical theorem-proving.
Synthesis Vis: A Web Site Supporting Collaborative Information Visualization

This paper describes the design and deployment of Synthesis Vis, an intranet web site where various users may contribute data, create interactive visualizations, and share visualizations. The goal of the site is to support collaboration around information visualizations at a large scale by fostering a social style of design process. Moreover, the site serves as a collaborative information visualization tool for individuals, providing a medium to share visualizations among users. To support this goal, the site includes novel mechanisms for enduser creation of visualizations and collaboration in the design process of those visualizations. The early usage of Synthesis Vis verifies the design and deployment of Synthesis Vis for collaborative information visualization.
Utility-Centric Networking: Balancing Transit Costs With Quality of Experience

This paper is focused on techniques for maximizing utility across all users within a total network transit cost budget. We present a new method for selecting between replicated servers distributed over the Internet. First, we introduce a novel utility framework that factors in quality of service metrics. Then we design an optimization algorithm, solvable in polynomial time, to allocate user requests to servers based on utility while satisfying network transit cost constraints, mapping service names to service instance locators. We then describe an efficient, low overhead distributed model which only requires knowledge of a fraction of the data required by the global optimization formulation. Next, a load-balancing variant of the algorithm is explored that substantially reduces blocking caused by congested servers. Extensive simulations show that our method is scalable and leads to higher user utility compared with mapping user requests to the closest service replica, while meeting network traffic cost constraints. We discuss several options for real-world deployment that require no changes to end-systems based on either the use of SDN controllers or extensions to the current DNS system.
Adding items that assess changes in activities of daily living does not improve the predictive accuracy of the Palliative Prognostic Index

Background: Changes in activities of daily living in cancer patients may predict their survival. The Palliative Prognostic Index is a useful tool to evaluate cancer patients, and adding an item about activities of daily living changes might improve its predictive value. Aim: To clarify whether adding an item about activities of daily living changes improves the accuracy of Palliative Prognostic Index. Design: Multicenter prospective cohort study. Setting: A total of 58 palliative care services in Japan. Participants: Patients aged >20 years diagnosed with locally extensive or metastatic cancer (including hematological neoplasms) who had been admitted to palliative care units, were receiving care by hospital-based palliative care teams, or were receiving home-based palliative care. Palliative care physicians recorded clinical variables at the first assessment and followed up patients 6 months later. Results: A total of 2425 subjects were recruited and 2343 of these had analyzable data. The C-statistic of the original Palliative Prognostic Index was 0.801, and those of modified Palliative Prognostic Indices ranged from 0.793 to 0.805 at 3 weeks. For 6-week survival predictions, the C-statistic of the original Palliative Prognostic Index was 0.802, and those of modified Palliative Prognostic Indices ranged from 0.791 to 0.799. The weighted kappa of the original Palliative Prognostic Index was 0.510, and those of modified Palliative Prognostic Indices ranged from 0.484 to 0.508. Conclusion: Adding items about activities of daily living changes to the Palliative Prognostic Index did not improve prognostic value in advanced cancer patients.
Blueprints of a lightweight automated experimentation system: a building block towards experimental cyber security

Many research projects studying security threats require realistic network scenarios while dealing with millions of cyber threats (e.g., exploit programs and malware). For instance, studying the execution of malware may require to take into account different network configurations in which malware can propagate, as well as dealing with thousands (or millions) of different malware samples. The same challenge occurs if one wants to evaluate IDSs, study exploit programs or conduct vulnerability assessment using realistic network scenarios. Moreover, cyber threats are highly dynamic. Every day, new vulnerabilities are identified and documented in software commonly used by computers connected to the Internet, and new malware instances and exploit programs are also identified. Consequently, it is not viable to develop (deploy) an environment every time cyber threats or security products (e.g., IDSs and anti-virus) have to be studied from a different perspective. New research methodologies and tools are needed to systematically conduct cyber security research. Automation is required to deal with the increasingly large number of cyber threats. In this paper, we draw the foundations of an experimental approach to cyber security by providing the blueprints of a lightweight Automated Experimentation System (AES). The AES automatically executes experiments based on a specification file. We describe its usage in different network security research projects, from IDS evaluation to static and dynamic malware analysis. The results we derived from these different research projects show that our experimental approach to cyber security, enabled by the AES, enhances the scope (and scale) of research in this field. Consequently, the AES improves our understanding of cyber threats and our assessment of the current state of security products.
A compact dual-polarized magneto-electric dipole antenna for 2G/3G/LTE applications

A compact ±45° dual-polarized magneto-electric (ME) dipole base station antenna is proposed for 2G/3G/LTE applications. The antenna is excited by two Γ-shaped probes placed at a convenient location and two orthogonally octagonal loop electric dipoles are employed to achieve a wide impedance bandwidth. A stable antenna gain and a stable radiation pattern are realized by using a rectangular box-shaped reflector instead of planar one. The antenna is prototype and measured. Measured results show overlapped impedance bandwidth is 58% with standing-wave ratio (SWR) ≤ 1.5 from 1.68 to 3.05 GHz, port-to-port isolation is large than 26 dB within the bandwidth, and stable antenna gains of 8.6 ± 0.8 dBi and 8.3 ± 0.6 dBi for port 1 and port 2, respectively. Nearly symmetrical radiation patterns with low back lobe radiation both in horizontal and vertical planes, and narrow beamwidth can be also obtained. Moreover, the size of the antenna is very compact, which is only 0. 79λ0 × 0. 79λ0 × 0. 26λ0. The proposed antenna can be used for multiband base stations in next generation communication systems.
Divergent bornaviruses from Australian carpet pythons with neurological disease date the origin of extant Bornaviridae prior to the end-Cretaceous extinction

Tissue samples from Australian carpet pythons (Morelia spilota) with neurological disease were screened for viruses using next-generation sequencing. Coding complete genomes of two bornaviruses were identified with the gene order 3’-N-X-P-G-M-L, representing a transposition of the G and M genes compared to other bornaviruses and most mononegaviruses. Use of these viruses to search available vertebrate genomes enabled recognition of further endogenous bornavirus-like elements (EBLs) in diverse placental mammals, including humans. Codivergence patterns and shared integration sites revealed an ancestral laurasiatherian EBLG integration (77 million years ago [MYA]) and a previously identified afrotherian EBLG integration (83 MYA). The novel python bornaviruses clustered more closely with these EBLs than with other exogenous bornaviruses, suggesting that these viruses diverged from previously known bornaviruses prior to the end-Cretaceous (K-Pg) extinction, 66 MYA. It is possible that EBLs protected mammals from ancient bornaviral disease, providing a selective advantage in the recovery from the K-Pg extinction. A degenerate PCR primer set was developed to detect a highly conserved region of the bornaviral polymerase gene. It was used to detect 15 more genetically distinct bornaviruses from Australian pythons that represent a group that is likely to contain a number of novel species.
Characterization and Epitope Mapping of the Polyclonal Antibody Repertoire Elicited by Ricin Holotoxin-Based Vaccination

ABSTRACT Ricin, one of the most potent and lethal toxins known, is classified by the Centers for Disease Control and Prevention (CDC) as a select agent. Currently, there is no available antidote against ricin exposure, and the most promising therapy is based on neutralizing antibodies elicited by active vaccination or that are given passively. The aim of this study was to characterize the repertoire of anti-ricin antibodies generated in rabbits immunized with ricin toxoid. These anti-ricin antibodies exhibit an exceptionally high avidity (thiocyanate-based avidity index, 9 M) toward ricin and an apparent affinity of 1 nM. Utilizing a novel tissue culture-based assay that enables the determination of ricin activity within a short time period, we found that the anti-ricin antibodies also possess a very high neutralizing titer. In line with these findings, these antibodies conferred mice with full protection against pulmonary ricinosis when administered as a passive vaccination. Epitope mapping analysis using phage display random peptide libraries revealed that the polyclonal serum contains four immunodominant epitopes, three of which are located on the A subunit and one on the B subunit of ricin. Only two of the four epitopes were found to have a significant role in ricin neutralization. To the best of our knowledge, this is the first work that characterizes these immunological aspects of the polyclonal response to ricin holotoxin-based vaccination. These findings provide useful information and a possible strategy for the development and design of an improved ricin holotoxin-based vaccine.
Embodied Evolution in Collective Robotics: A Review

This article provides an overview of evolutionary robotics techniques applied to online distributed evolution for robot collectives, namely, embodied evolution. It provides a definition of embodied evolution as well as a thorough description of the underlying concepts and mechanisms. This article also presents a comprehensive summary of research published in the field since its inception around the year 2000, providing various perspectives to identify the major trends. In particular, we identify a shift from considering embodied evolution as a parallel search method within small robot collectives (fewer than 10 robots) to embodied evolution as an online distributed learning method for designing collective behaviors in swarm-like collectives. This article concludes with a discussion of applications and open questions, providing a milestone for past and an inspiration for future research.
Iris recognition using minimum average correlation energy and principal component

Biometric systems have great importance in modern society. Today, we can find biometric systems using hardware technologies to provide an increasingly fast response. Partly this is possible due to the use of algorithms of digital signal processing which are used in these systems, such as the correlation filters. In this paper, we explore a change in correlation filters, using the principal component analysis, to provide robustness to the filters. Finally, the experiments demonstrate that the modification provides good results for a biometric recognition system human iris.
On-Demand based wireless resources trading for Green Communications

The purpose of Green Communications is to reduce the energy consumption of the communication system as much as possible without compromising the quality of service (QoS) for users. An effective approach for Green Wireless Communications is On-Demand strategy, which scales power consumption with the volume and location of user demand. Applying the On-Demand Communications model, we propose a novel scheme-Wireless Resource Trading, which characterizes the trading relationship among different wireless resources for a given number of performance metrics. According to wireless resource trading relationship, different wireless resources can be consumed for the same set of performance metrics. Therefore, to minimize the energy consumption for given performance metrics, we can trade the other type of wireless resources for the energy resource under the demanded performance metrics. Based on the wireless resource trading relationship, we derive the optimal energy-bandwidth and energy-time wireless resource trading relationship for green wireless communications. We also develop an adaptive trading strategy by using different bandwidths or different delays for different transmission distances with available bandwidths and acceptable delay bounds in wireless networks. Our conducted simulations show that the energy consumption of wireless networks can be significantly reduced with our proposed wireless resources trading scheme.
A Comparative Analysis of Materialized Views Selection and Concurrency Control Mechanisms in NoSQL Databases

Relational databases are well suited for vertical scaling; however, specialized hardware can be expensive. Conversely, NewSQL and NoSQL data stores are designed to scale horizontally. NewSQL databases provide ACID transaction support; however, joins are limited to the partition keys, resulting in restricted query expressiveness. On the other hand, NoSQL databases are designed to scale out on commodity hardware; however, they are limited by slow join performance. Hence, we consider if the NoSQL join performance can be improved while ensuring ACID semantics and without drastically sacrificing write performance, disk utilization and query expressiveness.This paper presents the Synergy system that leverages schema and workload driven mechanisms to identify materialized views, and a specialized concurrency control system on top of a NoSQL database to enable scalable data management with familiar relational conventions. Synergy trades slight write performance degradation and increased disk utilization for faster join performance (compared to standard NoSQL databases) and improved query expressiveness (compared to NewSQL databases).
On Hashing-Based Approaches to Approximate DNF-Counting

Propositional model counting is a fundamental problem in artificial intelligence with a wide variety of applications, such as probabilistic inference, decision making under uncertainty, and probabilistic databases. Consequently, the problem is of theoretical as well as practical interest. When the constraints are expressed as DNF formulas, Monte Carlo-based techniques have been shown to provide a fully polynomial randomized approximation scheme (FPRAS). For CNF constraints, hashing-based approximation techniques have been demonstrated to be highly successful. Furthermore, it was shown that hashing-based techniques also yield an FPRAS for DNF counting without usage of Monte Carlo sampling. Our analysis, however, shows that the proposed hashing-based approach to DNF counting provides poor time complexity compared to the Monte Carlo-based DNF counting techniques. Given the success of hashing-based techniques for CNF constraints, it is natural to ask: Can hashing-based techniques provide an efficient FPRAS for DNF counting? In this paper, we provide a positive answer to this question. To this end, we introduce two novel algorithmic techniques: \emph{Symbolic Hashing} and \emph{Stochastic Cell Counting}, along with a new hash family of \emph{Row-Echelon hash functions}. These innovations allow us to design a hashing-based FPRAS for DNF counting of similar complexity (up to polylog factors) as that of prior works. Furthermore, we expect these techniques to have potential applications beyond DNF counting.
Application of flipped classroom pedagogy to the human gross anatomy laboratory: Student preferences and learning outcomes

To improve student preparedness for anatomy laboratory dissection, the dental gross anatomy laboratory was transformed using flipped classroom pedagogy. Instead of spending class time explaining the procedures and anatomical structures for each laboratory, students were provided online materials to prepare for laboratory on their own. Eliminating in‐class preparation provided the opportunity to end each period with integrative group activities that connected laboratory and lecture material and explored clinical correlations. Materials provided for prelaboratory preparation included: custom‐made, three‐dimensional (3D) anatomy videos, abbreviated dissection instructions, key atlas figures, and dissection videos. Data from three years of the course (n = 241 students) allowed for analysis of students' preferences for these materials and detailed tracking of usage of 3D anatomy videos. Students reported spending an average of 27:22 (±17:56) minutes preparing for laboratory, similar to the 30 minutes previously allocated for in‐class dissection preparation. The 3D anatomy videos and key atlas figures were rated the most helpful resources. Scores on laboratory examinations were compared for the three years before the curriculum change (2011–2013; n = 242) and three years after (2014–2016; n = 241). There was no change in average grades on the first and second laboratory examinations. However, on the final semi‐cumulative laboratory examination, scores were significantly higher in the post‐flip classes (P = 0.04). These results demonstrate an effective model for applying flipped classroom pedagogy to the gross anatomy laboratory and illustrate a meaningful role for 3D anatomy visualizations in a dissection‐based course. Anat Sci Educ 11: 385–396. © 2017 American Association of Anatomists.
The Importance of inhibitors for the Simulation of metabolic Processes: in silico Zn2+ Inhibition of M-Aconitase from Analysis of glycolysis and Krebs Cycle Kinetic Models

Metal ions have a major effect on the metabolic processes in cells either as inhibitors or as integral components of enzymes. The inhibition of enzymes can take place either through the inhibition of gene expression or through inhibition of protein function. A particularly interesting example of the effect of a metal ion on metabolism is the observed inhibition of Krebs cycle and alteration of energy metabolism by zinc (II) cations. In this particular case metal ion inhibition of enzyme is linked to one of the major functions of prostate cells of accumulation and excretion of citrate. Experimental results have shown that increase in concentration of zinc (II) in prostate cells effectively blocks progression of a part of the Krebs cycle leading to change in the concentration of several metabolites with largest effect in the accumulation of citrate. Based on previously reported experimental results, several distinct mechanisms for zinc (II) inhibition of Krebs cycle were proposed. In order to determine the precise mechanism of inhibition in this system, a mathematical model of glycolysis and Krebs cycle was constructed. Three different types of inhibition were analyzed, including competitive and uncompetitive inhibition as well as inhibition through the alteration of the expression level of m-aconitase. The effects of different inhibition models on metabolite concentrations were investigated as a time course simulation of the system of reactions. Several kinetic parameters in the model were optimized in order to best resemble experimental measurements. The simulation shows that only competitive inhibition leads to an agreement with experimental data.
Regulation of T cell proliferation with drug-responsive microRNA switches

Abstract As molecular and cellular therapies advance in the clinic, the role of genetic regulation is becoming increasingly important for controlling therapeutic potency and safety. The emerging field of mammalian synthetic biology provides promising tools for the construction of regulatory platforms that can intervene with endogenous pathways and control cell behavior. Recent work has highlighted the development of synthetic biological systems that integrate sensing of molecular signals to regulated therapeutic function in various disease settings. However, the toxicity and limited dosing of currently available molecular inducers have largely inhibited translation to clinical settings. In this work, we developed synthetic microRNA-based genetic systems that are controlled by the pharmaceutical drug leucovorin, which is readily available and safe for prolonged administration in clinical settings. We designed microRNA switches to target endogenous cytokine receptor subunits (IL-2Rβ and γc) that mediate various signaling pathways in T cells. We demonstrate the function of these control systems by effectively regulating T cell proliferation with the drug input. Each control system produced unique functional responses, and combinatorial targeting of multiple receptor subunits exhibited greater repression of cell growth. This work highlights the potential use of drug-responsive genetic control systems to improve the management and safety of cellular therapeutics.
Functional analysis after rapid degradation of condensins and 3D-EM reveals chromatin volume is uncoupled from chromosome architecture in mitosis

ABSTRACT The requirement for condensin in chromosome formation in somatic cells remains unclear, as imperfectly condensed chromosomes do form in cells depleted of condensin by conventional methodologies. In order to dissect the roles of condensin at different stages of vertebrate mitosis, we have established a versatile cellular system that combines auxin-mediated rapid degradation with chemical genetics to obtain near-synchronous mitotic entry of chicken DT40 cells in the presence and absence of condensin. We analyzed the outcome by live- and fixed-cell microscopy methods, including serial block face scanning electron microscopy with digital reconstruction. Following rapid depletion of condensin, chromosomal defects were much more obvious than those seen after a slow depletion of condensin. The total mitotic chromatin volume was similar to that in control cells, but a single mass of mitotic chromosomes was clustered at one side of a bent mitotic spindle. Cultures arrest at prometaphase, eventually exiting mitosis without segregating chromosomes. Experiments where the auxin concentration was titrated showed that different condensin levels are required for anaphase chromosome segregation and formation of a normal chromosome architecture. This article has an associated First Person interview with the first author of the paper. Summary: Rapid condensin depletion reveals that different condensin levels are required for mitotic chromosome architecture and segregation. Condensin is not required for chromatin volume compaction during mitosis.