Miracle-dz/UniFAR-FTUs huggingface dataset:
Active exploration for robot parameter selection in episodic reinforcement learning

As the complexity of robots and other autonomous systems increases, it becomes more important that these systems can adapt and optimize their settings actively. However, such optimization is rarely trivial. Sampling from the system is often expensive in terms of time and other costs, and excessive sampling should therefore be avoided. The parameter space is also usually continuous and multi-dimensional. Given the inherent exploration-exploitation dilemma of the problem, we propose treating it as an episodic reinforcement learning problem. In this reinforcement learning framework, the policy is defined by the system's parameters and the rewards are given by the system's performance. The rewards accumulate during each episode of a task. In this paper, we present a method for efficiently sampling and optimizing in continuous multidimensional spaces. The approach is based on Gaussian process regression, which can represent continuous non-linear mappings from parameters to system performance. We employ an upper confidence bound policy, which explicitly manages the trade-off between exploration and exploitation. Unlike many other policies for this kind of problem, we do not rely on a discretization of the action space. The presented method was evaluated on a real robot. The robot had to learn grasping parameters in order to adapt its grasping execution to different objects. The proposed method was also tested on a more general gain tuning problem. The results of the experiments show that the presented method can quickly determine suitable parameters and is applicable to real online learning applications.
On the Comparative Performance Analysis of PAPR Reduction Techniques in OFDM System

Selected Mapping (SLM) and Partial Transmit Sequence (PTS) are two very well-known Peak-to-average Power Ratio (PAPR) reduction techniques for Orthogonal Frequency Division Multiplexing (OFDM) systems. Both these schemes show good PAPR reduction capabilities. However, for any PAPR reduction technique, the nature of spectral occupancy and the associated computational complexity also need to be taken into account when the overall performance is considered. In this paper, our goal is to perform a comparative performance analysis of SLM and PTS techniques by considering these three parameters, i.e. PAPR reduction, computational overhead and spectral compactness. For this, we at first look for the optimum values in terms of number of sequences in SLM and no. of sub-blocks in PTS. And then based on this finding, we perform performance analysis. Our finding shows that, PTS outperforms SLM when compared on the parameters mentioned above. Finally, to explore the feasibility of further improvement, we apply Walsh-Hadamard Transform to PTS scheme and show that it further reduces PAPR and improves spectral compactness.
Planetlab Overlay: Experimenting with Sensing and Actuation Support for Situated Autonomic Computing Services for the Planetary- Scale System

A liquid feed composition for cattle is disclosed which is capable of controlling consumption by cattle to a desired level without the use of equipment for this purpose. The liquid feed composition includes an intake limiting amount of an acidulated fat wherein acidulation of the fat is carried out at a temperature of at least about 220 DEG F. with a mineral acid.
TEACA: Thread ProgrEss Aware Coherence Adaption for hybrid coherence protocols

Hybrid coherence protocols can provide the scalability of directory protocols and low latency sharing miss handling in snooping protocols simultaneously. Unfortunately, how to adapt the hybrid protocols at runtime is not well studied. This paper proposes Thread ProgrEss Aware Coherence Adaption (TEACA) which utilizes the thread progress information as the hints to adapt hybrid coherence protocols. Specifically, TEACA fuses the memory system statistics to estimate the progress of threads. Based on the estimated thread progress information, TEACA dynamically categorizes threads into leader threads and laggard threads. The thread categorization decisions are then leveraged for efficient coherence adaption in hybrid coherence protocols. A case study on a recently proposed hybrid protocol (PATCH [29]) shows that, with the hints from TEACA, the enhanced hybrid protocol outperforms its baseline in both application execution time and energy dissipation.
Mind, mousse and moderation

This chapter is about the ways that psychology appears in, and is used in, the process of research. More particularly we will be considering the way psychological terms, orientations, constructions, and displays are manifest, and practically drawn on, in market research focus groups. This study reflects a broader concern with what psychology is for in the different practices, everyday and institutional, intimate and public, that it appears. The interest here is to contribute to the literature on method as an interactional and discursive accomplishment and at the same time to contribute to the broader literature of discursive psychology. We will start with some comments on the general approach of discursive psychology and then consider research on the interactional accomplishment of research methods.
Using Scalloped Sectors to Generate Poisson-Disk Sampling Patterns

Sampling distributions with blue noise characteristics are widely used in computer graphics. Although Poisson-disk distributions are known to have excellent blue noise characteristics, they are generally regarded as too computationally expensive to generate in real time. We present a new data structure that alllows sampling by dart-throwing in O(N logN) time. We also show how a novel and efficient variation on this algorithm can be used to generate Poissondisk distributions in O(N) time and space.
A redefinition of the syndrome of Broca's aphasia: Implications for a neuropsychological model of language

ABSTRACT A neuropsychological theory is offered to account for the syndrome of Broca's aphasia. A critical review of the literature, with emphasis on recent research, provides the basis for a redefinition of the syndrome that considerably broadens its classical description. The argument is advanced that the focus of neuropsychological explanation should be on theoretically separable psychological mechanisms that might be disrupted in relative isolation from other components in conditions of focal brain damage, rather than on isolated units of aphasic performance. The symptoms that characterize Broca's aphasia are explained as predictable behavioral manifestations of a central disruption of the syntactic parsing component of the language System, coupled with a (theoretically independent) articulatory deficit that affects only the speech output System. The neuroanatomical implications of this argument are considered within the framework of the classical “strong localizationist” hypothesis.
Happiness in severe mental illness: exploring subjective wellbeing of individuals with psychosis and encouraging socially inclusive multidisciplinary practice

Purpose – This paper seeks to extend the focus of positive psychology research to individuals with severe mental illness (SMI) to address an aspect of social exclusion experienced by this disadvantaged client group.Design/methodology/approach – The article summarises and builds on the outcomes of an earlier subjective wellbeing in psychosis study and arrives at original implications to challenge socially exclusive assumptions about limited emotional capabilities of those with SMI. The authors make suggestions for enhancing the wellbeing of people with SMI from the perspective of social inclusion. Data were gathered through validated self‐report rating scales and analysed statistically.Findings – The levels of subjective wellbeing within the sample were shown to approximate those established in the general population. Depression was demonstrated to mediate the effects that the experience of psychosis had on participants' life satisfaction. Psychosis did not appear to prevent individuals from experiencing h.
Pointable: an in-air pointing technique to manipulate out-of-reach targets on tabletops

Selecting and moving digital content on interactive tabletops often involves accessing the workspace beyond arm's reach. We present Pointable, an in-air, bimanual perspective-based interaction technique that augments touch input on a tabletop for distant content. With Pointable, the dominant hand selects remote targets, while the non-dominant hand can scale and rotate targets with a dynamic C/D gain. We conducted 3 experiments; the first showed that pointing at a distance using Pointable has a Fitts' law throughput comparable to that of a mouse. In the second experiment, we found that Pointable had the same performance as multi-touch input in a resize, rotate and drag task. In a third study, we observed that when given the choice, over 75% of participants preferred to use Pointable over multi-touch for target manipulation. In general, Pointable allows users to manipulate out-of-reach targets, without loss of performance, while minimizing the need to lean, stand up, or involve collocated collaborators.
Purposeful Preparation

General and special education teachers are increasingly challenged by the prospect of collaborating in inclusive classrooms to meet the needs of all students. Unfortunately, few are prepared for such experiences. This study longitudinally explored elementary and special education pre-service teachers’ perceptions of inclusion as they partnered for a classroom management course and a field placement in K-5 classrooms. Statistical analyses of responses to the Attitudes toward Inclusion survey indicate statistically significant changes in the elementary pre-service teachers, but no change in the special education pre-service teachers. Implications for teacher educators are provided.
The Frequency of Methicillin-Resistant Staphylococcus aureus and Coagulase Gene Polymorphism in Egypt

The current study aimed to use Coagulase gene polymorphism to identify methicillin-resistant Staphylococcus aureus (MRSA) subtypes isolated from nasal carriers in Minia governorate, Egypt, evaluate the efficiency of these methods in discriminating variable strains, and compare these subtypes with antibiotypes. A total of 400 specimens were collected from nasal carriers in Minia governorate, Egypt, between March 2012 and April 2013. Fifty-eight strains (14.5%) were isolated and identified by standard microbiological methods as MRSA. The identified isolates were tested by Coagulase gene RFLP typing. Out of 58 MRSA isolates 15 coa types were classified, and the amplification products showed multiple bands (1, 2, 3, 4, 5, and 8 bands). Coagulase gene PCR-RFLPs exhibited 10 patterns that ranged from 1 to 8 fragments with AluI digestion. Antimicrobial susceptibility testing with a panel of 8 antimicrobial agents showed 6 different antibiotypes. Antibiotype 1 was the most common phenotype with 82.7%. The results have demonstrated that many new variants of the coa gene are present in Minia, Egypt, different from those reported in the previous studies. So surveillance of MRSA should be continued.
Joint Pricing and Production Control for a Manufacturer With Volume Flexibility

We consider a make-to-stock manufacturer that produces a single product and sells it through two different channels, one local and the other contractual. We determine how to manage production and pricing in the local channel in order to maximize the total expected discounted profit earned over an infinite time horizon. We characterize the optimal policy as comprising a base stock level for production control and a collection of thresholds for product pricing in the local channel.
Deep Abstraction and Weighted Feature Selection for Wi-Fi Impersonation Detection

The recent advances in mobile technologies have resulted in Internet of Things (IoT)-enabled devices becoming more pervasive and integrated into our daily lives. The security challenges that need to be overcome mainly stem from the open nature of a wireless medium, such as a Wi-Fi network. An impersonation attack is an attack in which an adversary is disguised as a legitimate party in a system or communications protocol. The connected devices are pervasive, generating high-dimensional data on a large scale, which complicates simultaneous detections. Feature learning, however, can circumvent the potential problems that could be caused by the large-volume nature of network data. This paper thus proposes a novel deep-feature extraction and selection (D-FES), which combines stacked feature extraction and weighted feature selection. The stacked autoencoding is capable of providing representations that are more meaningful by reconstructing the relevant information from its raw inputs. We then combine this with modified weighted feature selection inspired by an existing shallow-structured machine learner. We finally demonstrate the ability of the condensed set of features to reduce the bias of a machine learner model as well as the computational complexity. Our experimental results on a well-referenced Wi-Fi network benchmark data set, namely, the Aegean Wi-Fi Intrusion data set, prove the usefulness and the utility of the proposed D-FES by achieving a detection accuracy of 99.918% and a false alarm rate of 0.012%, which is the most accurate detection of impersonation attacks reported in the literature.
To seek or not to seek professional help? School leaders' dilemma

Purpose – School leaders are professionals who need professional help to enable them better to cope with the ever‐changing challenges characteristic to their daily routine. Yet, in considering their hierarchical position in schools, they may be reluctant to ask for professional assistance even when help is available and needed, attempting to maintain their power and firm image. The purpose of this study, therefore, is to explore how school leaders cope with this assumed dilemma.Design/methodology/approach – In‐depth open interviews were conducted with Israeli school principals. These interviews were structured around a set of key issues that the literature identified as being related to help‐seeking behavior.Findings – Data indicate principals' loneliness on the job and need for professional help. Yet it appears that the threat implied in exposing one's weaknesses, lack of reliable sources of help within the formal system, personal inhibitions and fears of damaging self‐image and losing capacity to influe.
Growing Oranges on Mozart's Apple Tree: Inner Form and Aesthetic Judgment

MUSIC T HEORISTS O FTEN P RESUME that the sections of a musical masterwork match organically, enhancing unity and value. This “inner form” should be distinguished from coherence associated with inter-opus constraints, such as conventional forms. Studies indicate that violating inter-opus constraints hardly affects listeners’ aesthetic judgments. Here we examine how violating inner form affects such judgments. Musically trained and untrained listeners heard the intact opening movements of Mozart’s piano sonatas, K. 280 and 332, as well as hybrids mixing sections from these two movements while maintaining overall form and tonal structure. Participants rated originals and hybrids on aesthetically relevant scales (e.g., liking, coherence, interest), after a single hearing and following extended exposure. Results show no significant preference for originals, even after repeated hearings. Music training tended to enhance preference for hybrid over original. Thus, inner form and its supposed organic unity, presumed tenets of musical genius, may not affect listeners’ evaluation.
Deliberative institutional economics, or DoesHomo oeconomicus argue? A proposal for combining new institutional economics with discourse theory

Institutional economics and discourse theory stand unconnected next to each other, in spite of the fact that they both ask for the legitimacy of institutions (normative) and the functioning and effectiveness of institutions (positive). Both use as theoretical constructions rational individuals and the concept of consensus for legitimacy. Whereas discourse theory emphasizes the conditions of a legitimate consensus and could thus enable institutional economics to escape the infinite regress of judging a consensus legitimate, institutional economics has a tested social science paradigm (rational choice) of explaining and predicting the functioning of institutions. The article outlines a theoretical synthesis of the two theories by finding points in common and possibilities of fruitful combinations concerning the problem of legitimacy, institutional design and effectiveness of legal norms.
Athena: A New Code for Astrophysical MHD

A new code for astrophysical magnetohydrodynamics (MHD) is described. The code has been designed to be easily extensible for use with static and adaptive mesh refinement. It combines higher order Godunov methods with the constrained transport (CT) technique to enforce the divergence-free constraint on the magnetic field. Discretization is based on cell-centered volume averages for mass, momentum, and energy, and face-centered area averages for the magnetic field. Novel features of the algorithm include (1) a consistent framework for computing the time- and edge-averaged electric fields used by CT to evolve the magnetic field from the time- and area-averaged Godunov fluxes, (2) the extension to MHD of spatial reconstruction schemes that involve a dimensionally split time advance, and (3) the extension to MHD of two different dimensionally unsplit integration methods. Implementation of the algorithm in both C and FORTRAN95 is detailed, including strategies for parallelization using domain decomposition. Results from a test suite which includes problems in one-, two-, and three-dimensions for both hydrodynamics and MHD are given, not only to demonstrate the fidelity of the algorithms, but also to enable comparisons to other methods. The source code is freely available for download on the web.
Survival of Staphylococcus pseudintermedius in modified Romanowsky staining solutions

BACKGROUND Stains that are used regularly for patient-side diagnosis to rapidly identify bacterial and fungal infections could become contaminated by common pathogens, such as Staphylococcus pseudintermedius, during slide immersion. HYPOTHESIS/OBJECTIVES To determine whether the inoculation of S. pseudintermedius into modified Romanowsky type stains (Quick Dip® ) results in viable bacterial contamination and whether this is influenced by the addition of organic debris (canine hair and skin). METHODS A clinical isolate of S. pseudintermedius was inoculated into clean and organically contaminated Quick Dip® solutions (methanol fixative, eosin, methylene blue), and positive (broth) and negative (bleach) controls. Each solution was tested for the presence of viable bacteria by counting the number of colony forming units (CFU/mL) at various time points. Solutions also were examined under high power microscopy to count the number of visible bacteria at each time point. RESULTS Staphylococcus pseudintermedius was able to survive in the clean and contaminated Quick Dip® stains for at least one hour, but by 24 h no viable bacteria remained. Survival of the bacteria was not supported in the fixative at any time point. Staphylococcus pseudintermedius remained visible under high power microscopy for up to 2 weeks in all organically contaminated solutions of the Quick Dip® set. CONCLUSIONS AND CLINICAL IMPORTANCE Staphylococcus pseudintermedius only remains viable in eosin and methylene blue for short periods of time, but the prolonged visibility of dead organisms could theoretically lead to the misdiagnosis of cytology samples.
Anomaly Localization in Topic-Based Analysis of Surveillance Videos

Topic-models for video analysis have been used for unsupervised identification of normal activity in videos, thereby enabling the detection of anomalous actions. However, while intervals containing anomalies are detected, it has not been possible to localize the anomalous activities in such models. This is a challenging problem as the abnormal content is usually a small fraction of the entire video data and hence distinctions in terms of likelihood are unlikely. Here we propose a methodology to extend the topic based analysis with rich local descriptors incorporating quantized spatio-temporal gradient descriptors with image location and size information. The visual clips over this vocabulary are then represented in latent topic space using models like pLSA. Further, we introduce an algorithm to quantify the anomalous content in a video clip by projecting the learned topic space information. Using the algorithm, we detect whether the video clip is abnormal and if positive, localize the anomaly in spatio-temporal domain. We also contribute one real world surveillance video dataset for comprehensive evaluation of the proposed algorithm. Experiments are presented on the proposed and two other standard surveillance datasets.
Stand by Your Man

Cultural values emphasizing female loyalty, sacrifice, and male honor may indirectly sanction relationship violence and reward women who remain in abusive relationships. Two studies compare participants from subcultures emphasizing honor (Latinos and southern Anglos in Study 1, Chileans in Study 2) and subcultures without strong honor traditions (northern U.S. Anglos in Study 1, Anglo-Canadians in Study 2). In Study 1, participants watch a videotape of a woman describing an abusive relationship. Participants from honor cultures are relatively more favorable to the woman if she stays in the relationship, compared to northerners. In Study 2, Chilean and Canadian students listen to audiotapes of a husband describing a violent conflict with his wife. Chileans rate the husband and his actions more positively than Canadians do when the conflict is jealousy related (perceived flirting), but no cultural differences are found when the conflict is unrelated to jealousy (spending too much money).
Counterintuition, existential anxiety, and religion as a by-product of the designing mind

In arguing for religion as a side effect of everyday cognition, Atran & Norenzayan (A&N) provide useful analyses of the strengths of the “naturalness-of-religion” position over others; however, experimental shortcomings limit the contributions of their empirical work. A relevant addendum involves considering research on children's orientation to teleological explanations of natural phenomena, which suggests that relatively rich cognitive proclivities might underlie religious thought.
Listening to Jack: GE's change conversations with shareholders

How organizations communicate with shareholders during times of great uncertainty, such as during transformational change, is a relatively neglected area within the change management literature. We use the concept of “change conversation” and speech act theory to analyze GE's letters to shareholders 1980‐1999. We found five consistent change conversations through which GE's management sought to reassure shareholders and reduce their uncertainty around the expected outcomes of GE's transformational changes: warnings; actions; explanations; achievements, and predictions. These were underpinned by three types of speech acts: assertives, expressives, and commissives. We suggest that internally and externally oriented change conversations differ, the former being best characterized as operational change conversations and the latter as supportive change conversations. We suggest that successful change managers engage in both types of change conversations.