Miracle-dz/UniFAR-FTUs huggingface dataset:
A decision theoretic approach for task coordination in social robots

We present a new method for designing and implementing socially interactive mobile robots built around a 3-layer hybrid control architecture. Our main contribution is at the deliberative level, where we introduce multiply sectioned Markov decision processes (MS-MDPs) as a mechanism for efficient task specification, policy generation and execution. Using MS-MDPs, we partition the task into a number of subtasks, each assigned to an MDP, such that each one can be specified and solved independently. Each MDP controls one aspect of the global task, and they all are executed concurrently, coordinated implicitly by common state variables. We validate our approach by presenting experiments performed using our robot HOMER, the human oriented messenger robot. HOMER is a stereo-vision guided mobile robot designed for performing a message delivery task, which allows for rich and complex robot-human interactions using a multi-modal interface. HOMER's deliberative layer includes 3 MDPs: the navigator, the dialogue manager and the gesture generator. Together they coordinate 10 behaviors for accomplishing the message delivery task.
Isolation and characterization of FliK-independent flagellation mutants from Salmonella typhimurium

A flagellum of Salmonella typhimurium and Escherichia coli consists of three structural parts, a basal body, a hook, and a filament. Because the fliK mutants produce elongated hooks, called polyhooks, lacking filament portions, the fliK gene product has been believed to be involved in both the determination of hook length and the initiation of the filament assembly. In the present study, we isolated two mutants from S. typhimurium which can form flagella even in the absence of the fliK gene product. Flagellar structures were fractionated from these suppressor mutants and inspected by electron microscopy. The suppressor mutants produced polyhook-filament complexes in the fliK mutant background, while they formed flagellar structures apparently indistinguishable from those of the wild-type strain in the fliK+ background. Genetic and sequence analyses of the suppressor mutations revealed that they are located near the 3'-end of the flhB gene, which has been believed to be involved in the early process of the basal body assembly. On the basis of these results, we discuss the mechanism of suppression of the fliK defects by the flhB mutations and propose a hypothesis on the export switching machinery of the flagellar proteins.
A frequency-scalable 15-bit incremental ADC for low power sensor applications

A 15-bit low-power incremental ADC is designed for sensor applications. The ADC is designed to be frequency-scalable by 1000 times from 1.67S/s to 1.67kS/s. To reduce power, an opamp with class AB characteristics is used. The design was fabricated in 0.18/Ltm CMOS and occupies an area of 0.35mm2. Configured to operate at full-rate as a Delta-Sigma modulator, the ADC achieves 91.8dB peak SNDR while consuming 83µW from a 1.8-V supply. Operating as an incremental converter, the ADC powers off periodically to achieve frequency scalability, maintaining 84.7dB to 88.9dB peak SNDR while operating from 1.67S/S to 1.67kS/s and scaling analog power by up to 500 times.
Notice of RetractionExpression of Human Interleukin-6 in Tobacco by Chloroplast Engineering

Chloroplast engineering has been developed as an important platform for biopharmaceutical proteins production. In this study, we aimed to introduce human interleukin-6 (IL-6) encoding sequence into tobacco chloroplast genome by chloroplast transformation and express the protein in plant chloroplasts. Expression vector pTRVIL6, which carries homologous fragment rp12-trnH-psbA-trnK of N. tabacum chloroplast genome, was constructed and used for biolistic bombardment of tobacco leaves. Two transplastomic lines were obtained. The results of PCR and southern blot analysis suggest that IL-6 gene has been inserted into the right site of tobacco chloroplast genome by homologous recombination and that the transformed tissuess have finished homoplasmy. RT-PCR analysis confirms that IL-6 gene is transcribed successfully in both lines. To our knowledge, this is the first report of IL-6 expression in plant. Production of IL-6 by plant would have high potential application.
Blame , What is it Good For ?

Blame is an vital social and cognitive mechanism that humans utilize in their interactions with other agents. In this paper, we discuss how blame-reasoning mechanisms are needed to enable future social robots to: (1) appropriately adapt behavior in the context of repeated and/or long-term interactions and relationships with other social agents; (2) avoid behaviors that are perceived to be rude due to inappropriate and unintentional connotations of blame; and (3) avoid behaviors that could damage long-term, working relationships with other social agents. We also discuss how current computational models of blame and other relevant competencies (e.g. natural language generation) are currently insufficient to address these concerns. Future work is necessary to increase the social reasoning capabilities of artificially intelligent agents to achieve these goals.
Delay and Capacity in Ad Hoc Mobile Networks with f-cast Relay Algorithms

The two-hop relay algorithm and its variants have been attractive for ad hoc mobile networks, because they are simple yet efficient, and more importantly, they enable the capacity and delay to be studied analytically. This paper considers a general two-hop relay with f-cast (2HR-f), where each packet is delivered to at most f distinct relay nodes and should be received in order at its destination. We derive the closed-form theoretical models rather than order sense ones for the 2HR-f algorithm with a careful consideration of the important interference, medium contention, traffic contention and queuing delay issues, which enable an accurate delay and capacity analysis to be performed for an ad hoc mobile network employing the 2HR-f. Based on our models, one can directly get the corresponding order sense results. Extensive simulation studies are also conducted to demonstrate the efficiency of these new models.
Application of robust, high-accuracy positioning for autonomous ground vehicles

In this paper we review the need for robust, high-accuracy positioning for path guidance in the presence of large structures (such as buildings and trees) and for the integration of sensor data. Such capability is necessary in many applications that require precision over vast areas of operation. We find that unless integrated tightly, combined INS/GPS systems diverge significantly when line of sight to GPS satellites is lost. This results in a long recovery period especially when cm level positioning is required. High-accuracy inertial sensing is also useful when registering sensor data taken from a moving vehicle. This is particularly the case when data from a scanning sensor must be integrated over time to form a composite picture that aids in detecting obstacles that would hinder an autonomous vehicle. We show how a tight integration between inertial sensing and GPS positioning resolves some issues in the loss and reacquisition of satellites and how the inertial positioning is used to register sensor data. We present results from two applications of autonomous ground vehicles that use integrated GPS/INS systems to follow prescribed paths [8] and to sense the environment around them [11, 12]. One operates in smooth terrains, and the other is intended for cross-country operation.
Etanercept (Enbrel) in the treatment of juvenile idiopathic arthritis

Introduction: Juvenile idiopathic arthritis (JIA) is a relatively common multidimensional and heterogeneous chronic disease of childhood. Children with JIA are at risk for significant morbidity in terms of joint damage, impairments in physical function and health-related quality of life. Outcomes for children with JIA have significantly improved with the use of biologic therapies in the past 15 years, with the most clinical experience being with etanercept. Areas covered: Basic pharmacokinetic and pharmacodynamic data for etanercept will be highlighted. This article will review the clinical trials and open-label registry data for the efficacy and safety of etanercept for use in JIA. Expert opinion: Etanercept is very effective for the treatment of JIA. Data from clinical trials and open-label studies support its clinical efficacy in 80% of patients which appears to be sustained over several years for the majority of treated patients. The safety profile is also acceptable with a serious adverse event rate of 0.03 – 0.12 per patient-year. Further research is needed to evaluate any possible link between biologic therapy, JIA and malignancy, to obtain more long-term safety data, and to document improvements in quality of care and cost-benefit for associated with biologic therapies which may additionally assist in access to these medications. Further, identification of potential clinical or laboratory markers allowing for prediction of response and timing of starting and cessation of this biologic therapy are urgently required.
Unambiguous ultrashort pulse reconstruction from double spectrograms alone

We report a spectrographic technique for amplitude and phase measurements of ultrashort laser pulses (above 10 fs). Pulse information is obtained directly from two different spectrograms, using the mathematical relations between Wigner–Ville function projections. Pulses are reconstructed rapidly and unambiguously without stagnation. This non-interferometric method is demonstrated experimentally for the successful characterization of 100 fs pulses.
Clinical experimentation with aerosol antibiotics: current and future methods of administration

Currently almost all antibiotics are administered by the intravenous route. Since several systems and situations require more efficient methods of administration, investigation and experimentation in drug design has produced local treatment modalities. Administration of antibiotics in aerosol form is one of the treatment methods of increasing interest. As the field of drug nanotechnology grows, new molecules have been produced and combined with aerosol production systems. In the current review, we discuss the efficiency of aerosol antibiotic studies along with aerosol production systems. The different parts of the aerosol antibiotic methodology are presented. Additionally, information regarding the drug molecules used is presented and future applications of this method are discussed.
John Searle and the Construction of Social Reality

Introduction 1. Creating Institutional Reality: Dreyfus on Searle 2. Institutional Atomism: Hacking on Searle 3. Two criticisms of Institutional Atomism. 4. The Structure of Social Scientific Revolutions: Kuhn and Weber 5. Searle and Weber: applications of the constitutive formula 6. Searle and Weber: the constitutive formula Bibliography Index.
Improving Efficiency of XPath-Based XML Querying

XML is becoming the de facto standard for information exchange. XML querying is a key component for structured information processing and plays a central role in the next generation world wide web, information management systems and databases. Applications relying on XML processing notably depend on XPath, the standard language for adressing parts of XML documents. Besides its fundamental functionality, reasons behind XPath suc- cess include being widely accepted by programmers and well-suited for formal treatments. With the growing volume of XML content and XML processing applications, our research is oriented toward efficiency of XML querying. Our approach relies on analysis and trans- formation of XPath expressions for optimization. This note presents current open issues with XPath, and introduces our preliminary results applied to streaming XPath processing. Moreover, it describes our methodology, which includes XPath modelisation using the Coq proof assistant, and future directions envisioned toward high performance XML querying.
COMPARATIVE STUDY OF INTELLIGENT TECHNIQUES FOR SOLVING OPF PROBLEM

In the present day scenario, of electrical power system engineering mainly encompasses the problem like optimal power flow. Optimal power flow problem are becoming increasingly stressed, and more difficult to operate. So, it is mandatory to overthrown these problems. This paper focuses on intelligent techniques and their comparative study for solving the optimal power flow problem. These techniques includes Artificial neural network (ANN) , Fuzzy logic(FL) , Genetic algorithm(GA), Particle swarm optimization (PSO) , Ant colony optimization (ACO),Differential evolution(DE) , Artificial bee colony(ABC). This paper first accord a brief review to these techniques then observations on the pros and cons and lastly shows a comparison of all Intelligent Techniques.
Single-view hair modeling for portrait manipulation

Human hair is known to be very difficult to model or reconstruct. In this paper, we focus on applications related to portrait manipulation and take an application-driven approach to hair modeling. To enable an average user to achieve interesting portrait manipulation results, we develop a single-view hair modeling technique with modest user interaction to meet the unique requirements set by portrait manipulation. Our method relies on heuristics to generate a plausible high-resolution strand-based 3D hair model. This is made possible by an effective high-precision 2D strand tracing algorithm, which explicitly models uncertainty and local layering during tracing. The depth of the traced strands is solved through an optimization, which simultaneously considers depth constraints, layering constraints as well as regularization terms. Our single-view hair modeling enables a number of interesting applications that were previously challenging, including transferring the hairstyle of one subject to another in a potentially different pose, rendering the original portrait in a novel view and image-space hair editing.
On global external stochastic stabilization of linear systems with input saturation

We consider the problem of global external stochastic stabilization for linear plants with saturating actuators, driven by a stochastic external disturbance, and having random Gaussian-distributed initial conditions. The aim of this stabilization is to control such plants by a possibly nonlinear static state feedback law that achieves global asymptotic stability in the absence of disturbances, while guaranteeing a bounded variance of the state vector for all time in the presence of disturbances and Gaussian distributed initial conditions. Results for continuous-time open-loop critically stable plants have been obtained before. The goal of this paper is to extend this result to critically unstable plants. We view our contribution in this paper as a first critical step in solving the LQG control problem for linear systems subject to saturated inputs which is a research problem with a long history in our field.
Acute effects of cocaine on the neurobiology of cognitive control

Compromised ability to exert control over drug urges and drug-seeking behaviour is a characteristic of addiction. One specific cognitive control function, impulse control, has been shown to be a risk factor for the development of substance problems and has been linked in animal models to increased drug administration and relapse. We present evidence of a direct effect of cocaine on the neurobiology underlying impulse control. In a laboratory test of motor response inhibition, an intravenous cocaine administration improved task performance in 13 cocaine users. This improvement was accompanied by increased activation in right dorsolateral and inferior frontal cortex, regions considered critical for this cognitive function. Similarly, for both inhibitory control and action monitoring processes, cocaine normalized activation levels in lateral and medial prefrontal regions previously reported to be hypoactive in users relative to drug-naive controls. The acute amelioration of neurocognitive dysfunction may reflect a chronic dysregulation of those brain regions and the cognitive processes they subserve. Furthermore, the effects of cocaine on midline function suggest a dopaminergically mediated intersection between cocaine's acute reinforcing effects and its effects on cognitive control.
Enhancing the search ability of differential evolution through competent leader

In the field of evolutionary algorithm EA, differential evolution DE is successfully used in various scientific and engineering fields due to its strong global optimisation capability and simple implementation. However, in most of DE, the search is guided by the random or local optimal vectors. That is, DE does not effectively use the good information of population to guide the search. Therefore, to alleviate this drawback and enhance the search ability of DE, a competent leaders guiding strategy cLGS is proposed in this paper. The proposed cLGS is inspired by the natural phenomenon that good species usually contain useful information to guide the search of population. With the competent leaders, the good information of population can be utilised effectively during the evolutionary process. By incorporating cLGS into JADE which is a very competitive DE variant, the resulting algorithm, named JADE-cLGS, is proposed. In order to test the effectiveness of JADE-cLGS, a suite of benchmark functions is used. Experimental results demonstrate the high performance of JADE-cLGS by comparing with several DE variants.
The Entrepreneur 3 The Entrepreneur in Theory and Practice

Introduction The objective of this article is to advocate that economists devote more attention to factors concerning the supply of entrepreneurs both over time and across industries. The article has four main sections which reflect the structure of our case. First we follow the well-trodden track in pursuit of the entrepreneur within economic theory. Like others, we find a degree of definitional flexibility but also some indications that the track itself may be circular. However, the main point we wish to establish is that the emphasis has been on the entrepreneurial function and not on availability. The second section of the article acknowledges the plethora of empirical studies, couched in the neoclassical tradition, which equate the entrepreneurial function with the act of achieving entry to an industry. On balance we conclude that such studies have been rather unsuccessful in explaining new entry in part because they presume an unlimited supply of omniscient entry candidates. In the next section we develop the notion of the supply of entrepreneurs by considering the rather sporadic attempts to develop the microeconomics of entrepreneurial supply. The penultimate section adopts a different tack by going beyond the economics literature. Unlike the situation in economics, psychology and sociology have tended to concentrate on the supply of entrepreneurs. Consequently, we address the issue of what, if anything, economists can learn from psychological and sociological studies of entrepreneurship. Our conclusions outline an agenda for future research into the supply of entrepreneurs and pose practical questions which economists may wish to include in the work that they do.
Summarization System Integrated with Named Entity Tagging and IE pattern Discovery

We have introduced information extraction technique such as named entity tagging and pattern discovery to a summarization system based on sentence extraction technique, and evaluated the performance in the Document Understanding Conference 2001 (DUC-2001). We participated in the Single Document Summarization task in DUC-2001 and achieved one of the best performance in subjective evaluation of summarization results.
The Sliding Singular Spectrum Analysis: A Data-Driven Nonstationary Signal Decomposition Tool

Singular spectrum analysis (SSA) is a signal decomposition technique that aims at expanding signals into interpretable and physically meaningful components (e.g., sinusoids, noise, etc.). This paper presents new theoretical and practical results about the separability of the SSA and introduces a new method called sliding SSA. First, the SSA is combined with an unsupervised classification algorithm to provide a fully automatic data-driven component extraction method for which we investigate the limitations for components separation in a theoretical study. Second, the detailed automatic SSA method is used to design an approach based on a sliding analysis window, which provides better results than the classical SSA method when analyzing nonstationary signals with a time-varying number of components. Finally, the proposed sliding SSA method is compared to the empirical mode decomposition and to the synchrosqueezed short-time Fourier transform, applied on both synthetic and real-world signals.
Observer: an approach for query processing in global information systems based on interoperation across pre-existing ontologies

The huge number of autonomous and heterogeneous data repositories accessible on the "global information infrastructure" makes it impossible for users to be aware of the locations structure/organization, query languages and semantics of the data in various repositories. There is a critical need to complement current browsing, navigational and information retrieval techniques with a strategy that focuses on information content and semantics. In any strategy that focuses on information content, the most critical problem is that of different vocabularies used to describe similar information across domains. We discuss a scalable approach for vocabulary sharing. The objects in the repositories are represented as intensional descriptions by preexisting ontologies expressed in Description Logics characterizing information in different domains. User queries are rewritten by using interontology relationships to obtain semantics preserving translations across the ontologies.
Todd and Sen 1 MULTIPLE CRITERIA SCHEDULING USING GENETIC ALGORITHMS IN A SHIPYARD ENVIRONMENT

The main aim of scheduling large manufacturing processes is to minimise the time taken to manufacture the product from start to finish, and maximise the utilisation of machinery/ personnel. However, as the number of tasks increases it becomes more difficult to find good schedules within a reasonable time. This paper explains the development of a Multiple Criteria Genetic Algorithm (MCGA) scheduler which evolves good schedules based on several criteria. The system is then demonstrated using a shipyard steel-shop problem. INTRODUCTION In most large scale engineering projects production scheduling plays an important role in making efficient use of resources and reducing manufacturing time. Research in scheduling has traditionally concentrated on using heuristics, ordered search or applying mathematical algorithms. However, as the size of the scheduling task increases so does the difficulty of finding good solutions within a reasonable time. It is common to split the task into a hierarchy (levels of scheduling), where the highest level considers the main events (milestones) and the lowest level is scheduling of workstations. This makes the project more manageable. The high level scheduling is performed first and is used to set targets for the next level down. If these targets cannot be met then re-scheduling occurs. If suitable schedules still cannot be found work may be sub-contracted or resources increased with associated cost penalties. For a major project three or four levels may be required. In the case of Made-To-Order (MTO) products such as offshore structures and specialised marine vehicles there are additional constraints to handle. This increases the complexity even further. It is important to ensure that the processes of design, manufacture and assembly are integrated to their fullest extent to ensure the realisation of appropriate benefits. It is also often the case that orders are governed by strict deadlines with