Miracle-dz/UniFAR-FTUs huggingface dataset:
Behaviour-Based Reinforcement Learning

Abstract Although behaviour-based robotics has been successfully used to develop autonomous mobilerobots up to a certain point, further progress may require the integration of a learning model intothe behaviour-based framework. Reinforcement learning is a natural candidate for this becauseit seems well suited to the problems faced by autonomous agents. However, previous attemptsto use reinforcement learning in behaviour-based mobile robots have been simple combinationsof these two methodologies rather than full integrations, and have suffered from severe scalingproblems that appear to make them infeasible. Furthermore, the implicit assumptions that formthe basis of reinforcement learning theory were not developed with the problems faced byautonomous agents in complex environments in mind.This dissertation introduces a model of reinforcement learning that is designed speciﬁcally foruse in behaviour-based robots, taking the conditions faced by situated agents into account. Themodel layers a distributed and asynchronous reinforcement learning algorithm over a learnedtopological map and standard behavioural substrate to create a reinforcement learning complex.The topological map creates a small and task-relevant state space that aims to make reinforce-ment learning feasible, while the distributed and asynchronous nature of the model makes itcompatible with behaviour-based design principles.The model is then validated through an experiment that requires a mobile robot to performpuck foraging in three separate artiﬁcial arenas. The development of Dangerous Beans, amobile robot that is capable of building a distributed topological map of its environment andperforming reinforcement learning over it is described, along with the results of its use to testthree control strategies (random decision making, a standard reinforcement learning algorithmlayered on top of a topological map, and the full model developed in this dissertation) in thearenas. The results show that the model developed in this dissertation is able to learn rapidlyin a real environment, and outperforms both the random strategy and the layered standardreinforcement learning algorithm. Following this, a discussion of the implications of theseresults is given, which suggests that situated learning and the integration of behaviour-basedmethods and layered learning models merit further study.i
What Happens after Conservation and Management Donors Leave? A Before and After Study of Coral Reef Ecology and Stakeholder Perceptions of Management Benefits

The coral reefs of Tanga, Tanzania were recognized as a national conservation priority in the early 1970s, but the lack of a management response led to damage by dynamite, beach seines, and high numbers of fishers until the mid 1990s. Subsequently, an Irish Aid funded IUCN Eastern Africa program operated from 1994 to mid 2007 to implement increased management aimed at reducing these impacts. The main effects of this management were to establish collaborative management areas, reduce dynamite and seine net fishing, and establish small community fisheries closures beginning in 1996. The ecology of the coral reefs was studied just prior to the initiation of this management in 1996, during, 2004, and a few years after the project ended in 2010. The perceptions of resource users towards management options were evaluated in 2010. The ecological studies indicated that the biomass of fish rose continuously during this period from 260 to 770 kg/ha but the small closures were no different from the non-closure areas. The benthic community studies indicate stability in the coral cover and community composition and an increase in coralline algae and topographic complexity over time. The lack of change in the coral community suggests resilience to various disturbances including fisheries management and the warm temperature anomaly of 1998. These results indicate that some aspects of the management program had been ecologically successful even after the donor program ended. Moreover, the increased compliance with seine net use and dynamite restrictions were the most likely factors causing this increase in fish biomass and not the closures. Resource users interviewed in 2010 were supportive of gear restrictions but there was considerable between-community disagreement over the value of specific restrictions. The social-ecological results suggest that increased compliance with gear restrictions is largely responsible for the improvements in reef ecology and is a high priority for future management programs.
Identification and characterization of ten new water gaps in seeds and fruits with physical dormancy and classification of water-gap complexes.

BACKGROUND AND AIMS Physical dormancy (PY) occurs in seeds or fruits of 18 angiosperm families and is caused by a water-impermeable palisade cell layer(s) in seed or fruit coats. Prior to germination, the seed or fruit coat of species with PY must become permeable in order to imbibe water. Breaking of PY involves formation of a small opening(s) (water gap) in a morpho-anatomically specialized area in seeds or fruits known as the water-gap complex. Twelve different water-gap regions in seven families have previously been characterized. However, the water-gap regions had not been characterized in Cucurbitaceae; clade Cladrastis of Fabaceae; subfamilies Bombacoideae, Brownlowioideae and Bythnerioideae of Malvaceae; Nelumbonaceae; subfamily Sapindoideae of Sapindaceae; Rhamnaceae; or Surianaceae. The primary aims of this study were to identify and describe the water gaps of these taxa and to classify all the known water-gap regions based on their morpho-anatomical features. METHODS Physical dormancy in 15 species was broken by exposing seeds or fruits to wet or dry heat under laboratory conditions. Water-gap regions of fruits and seeds were identified and characterized by use of microtome sectioning, light microscopy, scanning electron microscopy, dye tracking and blocking experiments. KEY RESULTS Ten new water-gap regions were identified in seven different families, and two previously hypothesized regions were confirmed. Water-gap complexes consist of (1) an opening that forms after PY is broken; (2) a specialized structure that occludes the gap; and (3) associated specialized tissues. In some species, more than one opening is involved in the initial imbibition of water. CONCLUSIONS Based on morpho-anatomical features, three basic water-gap complexes (Types-I, -II and -III) were identified in species with PY in 16 families. Depending on the number of openings involved in initial imbibition, the water-gap complexes were sub-divided into simple and compound. The proposed classification system enables understanding of the relationships between the water-gap complexes of taxonomically unrelated species with PY.
Private notes: encrypted XML notes synchronization and sharing with untrusted web services

Personal notes, even when shared with others, often contain highly sensitive information. From a security and privacy point of view, currently available (web) services that upload such personal notes to potentially untrusted third party servers are therefore problematic and we suggest to encrypt all notes before transferring them from the user's personal device. However, synchronization and sharing of encrypted data is a non-trivial issue, because conflict resolution and merging algorithms need to be applied to plain-text content. With Private Notes, we propose an architecture for client-side encryption, merge, and conflict handling of personal notes stored in XML format. We adopt the OpenPGP standard for symmetric and asymmetric encryption and Web-DAV for synchronizing and sharing notes on arbitrary web servers. Specific implementations in the form of a plug-in for the Tomboy desktop note taking application and the Android and iOS mobile platforms demonstrate the ease of use of encrypted notes sharing.
Local Numerical Range for a Class of 2 ⊗ d Hermitian Operators

Local numerical range is analyzed for a family of circulant observables and states of composite 2 ⊗ d systems. It is shown that for any 2 ⊗ d circulant operator $\mathcal{O}$ there exists a basis giving rise to the matrix representation with real nonnegative off-diagonal elements. In this basis the problem of finding the extremum of $\mathcal{O}$ on product vectors |x〉 ⊗ |y〉 ϵ ℂ2 ⊗ ℂd reduces to the corresponding problem in ℝ2 ⊗ ℝd. The final analytical result for d = 2 is presented.
Robust and Adaptive Estimation of State of Charge for Lithium-Ion Batteries

The reliable operation of battery management systems depends critically on the accurate estimation of the state of charge (SOC) and characterizing parameters of a battery system. SOC estimation employs models that must be robust against variations in battery cell electrochemical features, aging, and operating conditions. This paper reveals that commonly used SOC estimation schemes are fundamentally flawed in providing the robustness of SOC estimation against model uncertainties. Parameter estimation methodologies and adaptive SOC estimation design are introduced in this paper to enhance SOC estimation accuracy and robustness. By a scrutiny of the impact of parameter variations on SOC estimation accuracy, the SOC-open-circuit-voltage mapping is identified to be the most critical function that must be accurately established. Identification algorithms are introduced, and their convergence properties are established. The integration of the identification algorithms and SOC estimation schemes lead to an adaptive SOC estimation framework that is superior over the existing methods in providing much improved accuracy and robustness. Experimental studies are conducted to validate the algorithms.
New Challenges for Privacy Law: Wearable Computers that Create Electronic Digital Diaries

Wearable computing technology developed and deployed in the next 15 years will create fundamental challenges to personal privacy law. This paper reviews current legal precedents in privacy and surveillance law and identifies some of the issues that courts will inevitably be asked to address. We focus on one particular capability of future mobile computing devices: the ability to act as long-term archiving devices and memory aids by continuously recording everyday experiences from on-body sensors such as cameras and microphones. We discuss how the law and social expectations may need to change to prevent the erosion of privacy protection as the use of wearable computing technology becomes pervasive throughout our society.
Vestibular Rehabilitation Therapy: Review of Indications, Mechanisms, and Key Exercises

Vestibular rehabilitation therapy (VRT) is an exercise-based treatment program designed to promote vestibular adaptation and substitution. The goals of VRT are 1) to enhance gaze stability, 2) to enhance postural stability, 3) to improve vertigo, and 4) to improve activities of daily living. VRT facilitates vestibular recovery mechanisms: vestibular adaptation, substitution by the other eye-movement systems, substitution by vision, somatosensory cues, other postural strategies, and habituation. The key exercises for VRT are head-eye movements with various body postures and activities, and maintaining balance with a reduced support base with various orientations of the head and trunk, while performing various upper-extremity tasks, repeating the movements provoking vertigo, and exposing patients gradually to various sensory and motor environments. VRT is indicated for any stable but poorly compensated vestibular lesion, regardless of the patient's age, the cause, and symptom duration and intensity. Vestibular suppressants, visual and somatosensory deprivation, immobilization, old age, concurrent central lesions, and long recovery from symptoms, but there is no difference in the final outcome. As long as exercises are performed several times every day, even brief periods of exercise are sufficient to facilitate vestibular recovery. Here the authors review the mechanisms and the key exercises for each of the VRT goals.
A Review On: Opinion Mining and Sentiment Analysis based on Natural Language Processing

marketing and advertising domains Opinion Mining is being larger domain. Advertiser needs to analyze performance/ popularity of ads that he/she posted on site. Star rating based mechanism may go fraud, because of robots or automatic responders. So, current system needs to be analyzed using comments & natural language processing. Fraud comments could be removed by using irrelevant comment removal mechanism suggested in paper. In this paper the role and importance of social networks as preferred environments for opinion mining and sentiment analysis are discussed especially. In this paper, selected properties of social networks that are relevant with respect to opinion mining are briefly described and outline the general relationships between the two disciplines. It presents the related work and provide basic definitions used in opinion mining area. Then, the original method of opinion classification is introduce and test the presented algorithm on real world datasets acquired from popular Polish social networks, reporting on the results. The results are outperform and soundly support the main issue of the paper, that social networks exhibit properties that make them very suitable for opinion mining activities. KeywordsSentiment, Domain-dependent corpus, Domain- independent corpus, Relevance.
Optics of Nanostructured Fractal Silver Colloids

Based on the theory of the optical properties of fractal clusters, which is an operator-based modification of the coupled-dipole method, an alternate solution is proposed for the problem of adequately describing the evolution of optical spectra of any polydisperse silver colloid with particles falling within the range of most characteristic sizes (5 - 30 nm). This is the range over which the results of the application of the well-known methods of classical electrodynamics, including the Mie theory, disagree with experimental data. The effect of variation of the parameters of such media on optical spectra is studied by a numerical simulation, which accounts for particle electrodynamic dipole-dipole interactions. Indeed, such interactions are shown to be a key factor in determining the broadening of the sol absorption spectra during the course of fractal aggregation. A quantitative explanation is given for the reasons for the appearance of individual specific features in the contours of the spectral absorption of different types of silver colloids.
Applicative Structures and Immediate Discourse in the Turkish Discourse Bank

Various discourse theories have argued for data structures ranging from the simplest trees to the most complex chain graphs. This paper investigates the structure represented by the explicit connectives annotated in the multiplegenre Turkish Discourse Bank (TDB). The dependencies that violate tree-constraints are analyzed. The effects of information structure in the surface form, which result in seemingly complex configurations with underlying simple dependencies, are introduced; and the structural implications are discussed. The results indicate that our current approach to local discourse structure needs to accommodate properly contained arguments and relations, and partially overlapping as well as shared arguments; deviating further from simple trees, but not as drastically as a chain graph structure would imply, since no genuine cases of structural crossing dependencies are attested in TDB.
RTS - an integrated analytic solution for managing regulation changes and their impact on business compliance

Governance, Risk Management and Compliance are key success factors for corporations. Every company worldwide must ensure a proper compliance level with current and future laws and regulations, but managing the dynamic nature of the regulatory environment is a challenge, for both small and medium business as well as large corporations. Specifically the challenge is knowing and interpreting which regulations impact a particular business. Governments and standard bodies keep producing new, revised legislation, and businesses today rely on employees and consultants for tracking and understanding impact on their operations. This paper introduces a novel prototype solution that addresses these concerns through the use of advanced text analytics. In particular the system is able to discover sources of regulatory content on the world wide web, track the changes to these regulations, extract metadata and semantic information and use these to provide a semantically guided comparison of regulation versions. Moreover, by leveraging the IBM DeepQA architecture, the solution is able to cross reference business objectives with the regulatory database and provide insights about the impact of new and revised laws on a company's business.
Humanism, the Hidden Curriculum, and Educational Reform: A Scoping Review and Thematic Analysis

Background Medical educators have used the hidden curriculum concept for over three decades to make visible the effects of tacit learning, including how culture, structures, and institutions influence professional identity formation. In response to calls to see more humanistic-oriented training in medicine, the authors examined how the hidden curriculum construct has been applied in the English language medical education literature with a particular (and centering) look at its use within literature pertaining to humanism. They also explored the ends to which the hidden curriculum construct has been used in educational reform efforts (at the individual, organizational, and/or systems levels) related to nurturing and/or increasing humanism in health care. Method The authors conducted a scoping review and thematic analysis that draws from the tradition of critical discourse analysis. They identified 1,887 texts in the literature search, of which 200 met inclusion criteria. Results The analysis documents a strong preoccupation with negative effects of the hidden curriculum, particularly the moral erosion of physicians and the perceived undermining of humanistic values in health care. A conflation between professionalism and humanism was noted. Proposals for reform largely target medical students and medical school faculty, with very little consideration for how organizations, institutions, and sociopolitical relations more broadly contribute to problematic behaviors. Conclusions The authors argue that there is a need to transcend conceptualizations of the hidden curriculum as antithetical to humanism and offer suggestions for future research that explores the necessity and value of humanism and the hidden curriculum in medical education and training.
Families, nurses and organisations contributing factors to medication administration error in paediatrics: a literature review

Background: Medication error is the most common adverse event for hospitalised children and can lead to significant harm. Despite decades of research and implementation of a number of initiatives, the error rates continue to rise, particularly those associated with administration. Objectives: The objective of this literature review is to explore the factors involving nurses, families and healthcare systems that impact on medication administration errors in paediatric patients. Design: A review was undertaken of studies that reported on factors that contribute to a rise or fall in medication administration errors, from family, nurse and organisational perspectives. The following databases were searched: Medline, Embase, CINAHL and the Cochrane library. The title, abstract and full article were reviewed for relevance. Articles were excluded if they were not research studies, they related to medications and not medication administration errors or they referred to medical errors rather than medication errors. Results: A total of 15 studies met the inclusion criteria. The factors contributing to medication administration errors are communication failure between the parents and healthcare professionals, nurse workload, failure to adhere to policy and guidelines, interruptions, inexperience and insufficient nurse education from organisations. Strategies that were reported to reduce errors were doublechecking by two nurses, implementing educational sessions, use of computerised prescribing and barcoding administration systems. Yet despite such interventions, errors persist. The review highlighted families that have a central role in caring for the child and therefore are key to the administration process, but have largely been ignored in research studies relating to medication administration. Conclusions: While there is a consensus about the factors that contribute to errors, sustainable and effective solutions remain elusive. To date, families have not been included as key stakeholders in researching or developing effective interventions to reduce medication administration errors. Implications for practice: • Future solutions to reduce medication errors need to take into account staffing levels, skill-mix, stress and workload • Organisations need to provide appropriate policies and guidelines as well as access to supportive technology and ongoing educational support aimed at reducing errors • Engaging nurses, doctors, pharmacists and, most importantly, families in developing practice through person-centred approaches is vital in order to improve the culture of medication safety and reduce medication errors
The Model of Software Process Measurement and Improvement Driven by Project Performance

In this paper on the basis of the existing model, Proposed project performance-driven process improvement framework and P-GQM model. The performance of products and process for process fragments are the metrics for the process objectives. It formalizes description of the achievement, goals, problems and the interrelationship between measurements, to measure results more accurately. Comprehensive reflects the software process or process fragment of the true state of operation, Software process improvement projects and provide a reliable basis, To facilitate timely project manager developed strategy to avoid risks, The model improve the success rate of
Drug Target Identification and Elucidation of Natural Inhibitors for Bordetella petrii: An In Silico Study

Environmental microbes like Bordetella petrii has been established as a causative agent for various infectious diseases in human. Again, development of drug resistance in B. petrii challenged to combat against the infection. Identification of potential drug target and proposing a novel lead compound against the pathogen has a great aid and value. In this study, bioinformatics tools and technology have been applied to suggest a potential drug target by screening the proteome information of B. petrii DSM 12804 (accession No. PRJNA28135) from genome database of National Centre for Biotechnology information. In this regards, the inhibitory effect of nine natural compounds like ajoene (Allium sativum), allicin (A. sativum), cinnamaldehyde (Cinnamomum cassia), curcumin (Curcuma longa), gallotannin (active component of green tea and red wine), isoorientin (Anthopterus wardii), isovitexin (A. wardii), neral (Melissa officinalis), and vitexin (A. wardii) have been acknowledged with anti-bacterial properties and hence tested against identified drug target of B. petrii by implicating computational approach. The in silico studies revealed the hypothesis that lpxD could be a potential drug target and with recommendation of a strong inhibitory effect of selected natural compounds against infection caused due to B. petrii, would be further validated through in vitro experiments.