Miracle-dz/UniFAR-FTUs huggingface dataset:
Discovering social interaction strategies for robots from restricted-perception Wizard-of-Oz studies

In this paper we propose a methodology for the creation of social interaction strategies for human-robot interaction based on restricted-perception Wizard-of-Oz studies (WoZ). This novel experimental technique involves restricting the wizard's perceptions over the environment and the behaviors it controls according to the robot's inherent perceptual and acting limitations. Within our methodology, the robot's design lifecycle is divided into three consecutive phases, namely data collection, where we perform interaction studies to extract expert knowledge and interaction data; strategy extraction, where a hybrid strategy controller for the robot is learned based on the gathered data; strategy refinement, where the controller is iteratively evaluated and adjusted. We developed a fully-autonomous robotic tutor based on the proposed approach in the context of a collaborative learning scenario. The results of the evaluation study show that, by performing restricted-perception WoZ studies, our robots are able to engage in very natural and socially-aware interactions.
A new non-uniform segmentation and addressing remapping strategy for hardware-oriented function evaluators based on polynomial approximation

This paper presents a new non-uniform segmentation method for arithmetic function evaluation based on polynomial approximations. The merging of several uniform segments can reduce the required ROM size compared with normal uniform segmentation. The previously proposed hierarchical segmentation turns out to be special cases of this new approach. In general, non-uniform segmentation leads to irregular address indexing that needs extra computation hardware. Here, an address rearrangement and mapping method is proposed that does not need any additional address computation, and thus the critical path delay can be reduced. Experimental results show that this new segmentation and address remapping method can efficiently reduce the table size for some elementary arithmetic functions, such as log2x and 1/x.
The Microstructure of Collaborative E-business Capability

IT has direct and observable positive effects for consumers. For firms, the situation is somewhat different, because efficiencies generated by publicly available technology tend to be competed away. Therefore, researchers from the strategy field and students of information systems have concluded that for firms, the opportunity lies in using IT better than competitors rather than in the technology itself. The thesis takes this conclusion as its premise and introduces the capability perspective to the study of collaborative B2B, a practice in which firms use IT to gain efficiencies and other benefits across organisational boundaries. Based on a literature review and an in-depth longitudinal case study of e-business at SCA Packaging, including three projects with customers, the thesis proposes a framework for the microstructure of collaborative e-business capability ? the CEBCAP-MS framework. The key categories in this framework are desired ends (the firm's motives for engaging in collaborative B2B), elements (the factors that enable attainment of desired ends) and flows to these elements (what management can do to develop collaborative e-business capability). The study supports the relevance of desired ends for e-business proposed in previous literature. Both efficiencies and lock-in effects are included among the motives that managers cite for engaging in collaborative B2B. The CEBCAP-MS framework points to six main elements that collectively influence the extent to which firms reach this potential: e-business applications, value system understanding, implementation, a collaborative foundation of the focal customer relationship, project evaluation and e-business organisation.
Cytochrome c assembly

Cytochromes c are central proteins in energy transduction processes by virtue of their functions in electron transfer in respiration and photosynthesis. They have heme covalently attached to a characteristic CXXCH motif via protein‐catalyzed post‐translational modification reactions. Several systems with diverse constituent proteins have been identified in different organisms and are required to perform the heme attachment and associated functions. The necessary steps are translocation of the apocytochrome polypeptide to the site of heme attachment, transport and provision of heme to the appropriate compartment, reduction and chaperoning of the apocytochrome, and finally, formation of the thioether bonds between heme and two cysteines in the cytochrome. Here we summarize the established classical models for these processes and present recent progress in our understanding of the individual steps within the different cytochrome c biogenesis systems. © 2013 IUBMB Life, 65(3):209–216, 2013
DNA Repair Enzyme Uracil DNA Glycosylase Is Specifically Incorporated into Human Immunodeficiency Virus Type 1 Viral Particles through a Vpr-Independent Mechanism

ABSTRACT The Vpr protein, encoded by the human immunodeficiency virus type 1 (HIV-1) genome, is one of the nonstructural proteins packaged in large amounts into viral particles. We have previously reported that Vpr associates with the DNA repair enzyme uracil DNA glycosylase (UDG). In this study, we extended these observations by investigating whether UDG is incorporated into virions and whether this incorporation requires the presence of Vpr. Our results, with highly purified viruses, show that UDG is efficiently incorporated either into wild-type virions or into Vpr-deficient HIV-1 virions, indicating that Vpr is not involved in UDG packaging. Using an in vitro protein-protein binding assay, we reveal a direct interaction between the precursor form of UDG and the viral integrase (IN). Finally, we demonstrate that IN-defective viruses fail to incorporate UDG, indicating that IN is required for packaging of UDG into virions.
On the marriage of Kolmogorov complexity and multi-fractal parameters for epileptic seizure classification

In this contribution, we propose a novel way of classification of normal and epileptic seizures in EEG signals based on the blending of Kolmogorov complexity measure and Multifractal analysis. Hurst Exponent has been used to model the long run interrelationship and Kolmogorov complexity measure to model the composite behavior of EEG signals. The utility of these two extracted features with machine learning tools like Decision trees, Naive Bayesian Classifier, KNN and SVM-based classification of normal and epileptic seizures with different kernels have been done. Performance results of the combined features from different methods validates the adequacy of the proposed methodology in seizure detection.
Elf5-centered transcription factor hub controls trophoblast stem cell self-renewal and differentiation through stoichiometry-sensitive shifts in target gene networks

Latos et al. demonstrate that precise levels of Elf5 are critical for normal expansion of the trophoblast stem cell (TSC) compartment and embryonic survival. Their data place Elf5 at the center of a stoichiometry-sensitive transcriptional network, where it acts as a molecular switch governing the balance between TSC proliferation and differentiation.
The Effects of Earnings and Firm Characteristics on Differential Interpretation of Earnings Announcements

This study examines whether differential interpretation of earnings announcements is affected by earnings and firm characteristics. We find that Kandel and Pearson's (1995) forecast measures of differential interpretation are: 1) negatively related to earnings predictability, firm size, and price-to-book ratio, and 2) positively related to earnings surprise, negative earnings, and analyst coverage. This evidence suggests that differential interpretation of earnings announcements is decreasing in the quality of the earnings, the quality of pre-announcement disclosure, and the cost of analyzing a firm's value.
French Gender Attribution on the Basis of Similarity: A Comparison Between AM and Connectionist Models

In simplistic terms the psychological literature on concept representation currently tends to favour either prototype or exemplar-based theories. Similar distinctions can be found within the computational literature. This paper examines the predictions of two such models in the domain of French gender attribution. The comparison between a standard feed-forward neural net model (prototype) and Analogical Modeling (exemplar) is of interest, aside from the broad issues of conceptual representation, since arguments have been presented by proponents of the latter theory as to its theoretical superiority over connectionist models on a variety of grounds. These claims are argued here to be either mistaken or less than compelling. It is, therefore, of some value to evaluate the two models on purely empirical grounds. A variety of simulations using a range of different representations and databases are compared with respect to their ability to generalise gender classifications to a set of unknown French nouns. Analysis shows that both models produce results which are not statistically significantly different.
Output-column folding for cellular-architecture FPGAs

The work described in this paper is a component of our comprehensive approach to the low-level synthesis (logic synthesis and layout synthesis) of Cellular-Architecture (CA-type) FPGAs. A multiple-output logic function is represented as a collection of complex terms. Each term is assigned to a separate row of a CA-type FPGA. These terms are collected using EXOR or OR gates to create function outputs, initially one output per column. In this paper an algorithm for multiple column folding of CA-type FPGAs is presented. The formulation of the problem is similar to the gate matrix layout problem but with additional constraints. Experimental results are very encouraging. <<ETX>>
IFP35 Is Involved in the Antiviral Function of Interferon by Association with the Viral Tas Transactivator of Bovine Foamy Virus

ABSTRACT Interferon-induced proteins (IFPs) exert multiple functions corresponding to diverse interferon signals. However, the intracellular functions of many IFPs are not fully characterized. Here, we report that IFP35, a member of the IFP family with a molecular mass of 35 kDa, can interact with the bovine Tas (BTas) regulatory protein of bovine foamy virus (BFV). The interaction involves NID2 (IFP35/Nmi homology domain) of IFP35 and the central domain of BTas. The overexpression of IFP35 disturbs the ability of BTas to activate viral-gene transcription and inhibits viral replication. The depletion of endogenous IFP35 by interfering RNA can promote the activation of BFV, suggesting an inhibitory function of IFP35 in viral-gene expression. In addition, IFP35 can interact with the homologous regulatory protein of prototype FV and arrest viral replication and repress viral transcription. Our study suggests that IFP35 may represent a novel pathway of interferon-mediated antiviral activity in host organisms that plays a role in the maintenance of FV latency.
A Control-based Approach Towards Adaptive Stream Processing Student :

Large-scale Internet-service providers such as Amazon, Google, Facebook, and Microsoft generate tens of millions of data events per second (Bailis et al. 2017). To handle such high throughput, they have traditionally resorted to offline batch systems, e.g., Spark SQL (Armbrust et al. 2015) and Hadoop MapReduce (Dean and Ghemawat 2008). More recently, however, there has been an increasing trend towards switching to online streaming systems to ensure timely processing and avoid the delays incurred by batching (Jindal et al. 2017; Meehan et al. 2017; Abraham et al. 2013). Fully achieving the benefits promised by these online systems, however, proved particularly challenging. To start with, event-based workloads exhibit high temporal and spatial variability, up to an order of magnitude compared to the average load (Kulkarni et al. 2015; NetFlix 2016). Further, due to the large number of servers involved, failures and hardware heterogeneity makes it hard to ensure stable and predictable performance. Together these issues significantly complicate resource provisioning, forcing system administrators to over-provision resources, with the obvious negative consequences on cost and complexity. An alternative and more efficient approach would be to dynamically modify the system reconfiguration (e.g., by adding/removing resources or by redistributing operators) whenever the workload or the environment changes. This would entail extending the streaming platform with a set of control policies and mechanisms that can reconfigure the
A survey on in-domain and cross-domain image classification using surf features

Image classification algorithms using state-of-the art methods have grabbed much attention in computer vision area. In-domain classification assumes the testing data to be in the same domain as of the training data. Cross-Domain classification is a paradigm where testing data is from a different but related domain to the training data. We use Speeded-Up Robust Features (SURF) for feature extraction, which outperforms other feature detectors in its speed and robustness. This paper implements in-domain and cross-domain classification for standard image datasets using benchmark algorithms and compare the efficiency of the algorithms to choose the best one for a particular combination of source and target datasets. In this paper we try to implement in-domain and cross-domain performances for standard images datasets using benchmark algorithms. And compare the efficacy of the algorithms to choose the optimized one for a particular combination of datasets. We assume the dataset to be available upfront.
A new dual output DC-DC converter with enhancing output voltage level

In this paper, a new dual output DC-DC converter is proposed. This topology is achieved from another dual output dc-dc converter with a little change. Conventional dual output converters provide two same level voltages in the outputs; but this topology provide two different voltage levels. In this topology, one of the output voltage gain has a considerable increment. This topology, uses two switches to perform the power conversion, without employing any transformers. The proposed topology can be used instead of two single output power supplies. Steady state analysis is described in details and finally simulation result in MATLAB Simulink environment for verification the theoretical analysis is proposed.
Characterization of Membrane‐Associated Peptidase Activities Expressed by Endothelial Cells of the Ovine Median Eminence

The capillary endothelial cells of the median eminence represent a potential site for the degradation/modification of both circulating and hypothalamic peptides passing through the hypophysial portal system toward the pituitary. This study examines endothelial cell peptidase expression in vitro by monitoring the metabolism of gonadotropin‐releasing hormone (GnRH) by cultured endothelial cells from sheep median eminence. Cleavage of GnRH by median eminence endothelial cell membranes generated GnRH1–5 as the primary stable product, which was then degraded to GnRH1–3 and free amino acids. Degradation of GnRH was completely inhibited by TPCK, ZnCI2 and N‐ethylmaleimide, and partially inhibited by EDTA and by a specific inhibitor of the metalloendopeptidase EC 3.4. 24.15, CFP‐AAY‐pAB. Interestingly, an increase in GnRH1–9 production was seen with the latter inhibitors, suggesting a two‐step mechanism of GnRH degradation involving a primary cleavage at the Pro9‐Gly10‐NH2 bond, inhibitable by TPCK, ZnCI2, and NEM, followed by cleavage by EC 3.4. 24.15 to generate GnRH1–5. Phosphoramidon and angiotensin converting enzyme inhibitors (as well as other non‐specific inhibitors) were without effect, indicating that endopeptidase EC 3.4. 24.11 and angiotensin converting enzyme are not involved. Neither bovine aortic endothelial cell nor AtT‐20 cell membranes exhibited this pattern of peptidase activity. Degradation of GnRH by intact median eminence endothelial cells in culture was also observed, suggesting an extracellular orientation for these enzymes; the potential role of such peptidases in the fine regulation of both pituitary function and local blood flow is currently under investigation.
Self-Management Programs: One Way to Promote Healthy Aging

The United States population is aging rapidly. In 2007, about 38 million people in America were aged 65 and older, about 13% of the population. That number is expected to nearly double by 2030 to an estimated 71.5 million Americans.1 Unfortunately, chronic illnesses often accompany the aging process. In 2002, the top three causes of death for U.S. adults aged 65 or older were heart disease (32% of all deaths), cancer (22%), and stroke (8%). These illnesses accounted for more than 60% of all deaths in this age group. Currently, at least 80% of older Ameri­ cans are living with at least one chronic condition, and 50% of them have at least two conditions.2 Not surprisingly, health-care expenditures increase as people age and their health deteriorates. Experts at the U.S. Department of Health and Human Ser­ vices (HHS) project that the cost of health care will reach $3.6 trillion in 2014, up from $2.2 trillion in 2007. The mean annual rate of growth of health-care costs through 2018 is projected to be 6.2%. Medicare spending grew 7.2% to $431 billion in 2007. Hospital expenditures grew 7.3% in 2007, up from 6.9% in 2006. It is projected that in 2018, Medicare spending will be nearly $935 billion.3 A number of older adults, especially members of racial/ethnic minority groups, have difficulty locating health-care services. In many communities, access to quality health services—and the costs of those services— remains a major obstacle for these and other segments of the population. To ease this problem of access and provide the needed comprehensive care to older Americans, the U.S. must more than triple the current number of clinicians with specialized geriatric training, according to the Alliance for Aging Research.4 Indeed, the U.S. has only about a quarter of the people needed to train students, residents, and physicians in geriatrics. Additionally, the need for community-based service programs will increase, including nutrition, physical fit­ ness, and fall prevention programs, which play a critical role in helping seniors to maintain and even improve their health. Many of the nation’s leading health-care experts are recommending a combination of clinical and community-based interventions to address the growing prevalence of chronic conditions. RADM Steven K. Galson, Acting Surgeon General
Art Appraisal Using Convolutional Neural Networks

The appraisal of artworks has long been an esoteric process reserved for the few educated in art and art history, yet it plays an integral role for collectors, curators, and auction houses. Valuation can be influenced by numerous factors and could be swayed by personal biases and local values. Machine learning algorithms may serve as a tool to adjudicate the value of artwork due to the high subjectivity of the pieces. In order to provide a more standardized method of appraising artwork, we suggest the use of a convolutional neural network (CNN), an algorithm typically used for image classification, to allow an individual without a background in art to better determine the market value of a given piece. We aim for the model to be free of the individual bias that are present in human art appraisers because the dataset is formed from many existing appraisals, averaging over the biases of multiple localities. Our hope is that upcoming artists, art buyers, and art sellers can make more informed decisions with the help of this model, and we may be able to determine cross-cultural features of art pieces that make them inherently valuable.
A systematic review of herbal medicinal products for the treatment of menopausal symptoms

ObjectiveMany women have turned to complementary and alternative medicines for relief from their menopausal symptoms. The prevalence of herbal medicinal product use among menopausal women highlights the need for investigation into these interventions. The aim of this study was to evaluate the benefit of herbal medicinal products for the treatment of menopausal symptoms by performing a systematic review of randomized clinical trials. DesignLiterature searches of four computerized databases were done to identify randomized clinical trials of herbal medicinal products for the treatment of menopausal symptoms. Manufacturers of herbal products were contacted, and our own files were also searched. There were no restrictions on the language of publication. Trials were considered if the outcome measures related to the physical or psychological impact of menopause, whether by compendium scores, questionnaires, or women's symptom diaries, excluding studies describing artificially induced menopause. This review was not concerned with biochemical or pathological data. ResultsEighteen randomized clinical trials that fit our criteria were identified. These studies investigated black cohosh (n = 4), red clover (n = 4), kava (n = 3), dong quai (n = 1), evening primrose oil (n = 1), ginseng (n = 1), and combination products (n = 4). Trial quality was generally good, with 16 of 18 studies scoring 3 or more (maximum 5) on the Jadad Scale. ConclusionsThere is no convincing evidence for any herbal medical product in the treatment of menopausal symptoms. However, the evidence for black cohosh is promising, albeit limited by the poor methodology of the trials. The studies involving red clover suggest it may be of benefit for more severe menopausal symptoms. There is some evidence for the use of kava, but safety concerns mean this herbal product is not a therapeutic option at present. The evidence is inconclusive for the other herbal medicinal products reviewed.
Application of permanent magnets in accelerators and electron storage rings (invited)

After an explanation of the general circumstances in which the use of permanent magnets in accelerators is desirable, a number of specific magnets will be discussed. That discussion includes magnets needed for the operation of accelerators as well as magnets that are employed for the utilization of charged particle beams, such as the production of synchrotron radiation.
A generic and fast C++ optimization framework

The development of the mlpack C++ machine learning library (this http URL) has required the design and implementation of a flexible, robust optimization system that is able to solve the types of arbitrary optimization problems that may arise all throughout machine learning problems. In this paper, we present the generic optimization framework that we have designed for mlpack. A key priority in the design was ease of implementation of both new optimizers and new objective functions to be optimized; therefore, implementation of a new optimizer requires only one method and implementation of a new objective function requires at most four functions. This leads to simple and intuitive code, which, for fast prototyping and experimentation, is of paramount importance. When compared to optimization frameworks of other libraries, we find that mlpack's supports more types of objective functions, is able to make optimizations that other frameworks do not, and seamlessly supports user-defined objective functions and optimizers.
Seasonal variability in nutritive value of ruminant diets under open grazing system in the semi-arid rangeland of Sudan (South Darfur State).

Seasonal variability in nutritive value of ruminant diets under open grazing system in the semi-arid rangeland of Sudan (South Darfur State) Awad O. Abusuwar and Elhadi O. Ahmed Dept. of Arid land Agriculture, Faculty of Meteorology, Environment and Arid land Agric. , King A/Aziz University, Jeddah/Saudi Arabia E-mail: abusuwar@yahoo.com Ennhod Desert Sheep Research Station, North Kordofan State/Sudan ABSTRACT