Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiagent Reinforcement Learning With Sparse Interactions by Negotiation and Knowledge Transfer

Reinforcement learning has significant applications for multiagent systems, especially in unknown dynamic environments. However, most multiagent reinforcement learning (MARL) algorithms suffer from such problems as exponential computation complexity in the joint state-action space, which makes it difficult to scale up to realistic multiagent problems. In this paper, a novel algorithm named negotiation-based MARL with sparse interactions (NegoSIs) is presented. In contrast to traditional sparse-interaction-based MARL algorithms, NegoSI adopts the equilibrium concept and makes it possible for agents to select the nonstrict equilibrium-dominating strategy profile (nonstrict EDSP) or meta equilibrium for their joint actions. The presented NegoSI algorithm consists of four parts: 1) the equilibrium-based framework for sparse interactions; 2) the negotiation for the equilibrium set; 3) the minimum variance method for selecting one joint action; and 4) the knowledge transfer of local ${Q}$ -values. In this integrated algorithm, three techniques, i.e., unshared value functions, equilibrium solutions, and sparse interactions are adopted to achieve privacy protection, better coordination and lower computational complexity, respectively. To evaluate the performance of the presented NegoSI algorithm, two groups of experiments are carried out regarding three criteria: 1) steps of each episode; 2) rewards of each episode; and 3) average runtime. The first group of experiments is conducted using six grid world games and shows fast convergence and high scalability of the presented algorithm. Then in the second group of experiments NegoSI is applied to an intelligent warehouse problem and simulated results demonstrate the effectiveness of the presented NegoSI algorithm compared with other state-of-the-art MARL algorithms.
Machine Learning for In Silico Virtual Screening and Chemical Genomics: New Strategies

Support vector machines and kernel methods belong to the same class of machine learning algorithms that has recently become prominent in both computational biology and chemistry, although both fields have largely ignored each other. These methods are based on a sound mathematical and computationally efficient framework that implicitly embeds the data of interest, respectively proteins and small molecules, in high-dimensional feature spaces where various classification or regression tasks can be performed with linear algorithms. In this review, we present the main ideas underlying these approaches, survey how both the “biological” and the “chemical” spaces have been separately constructed using the same mathematical framework and tricks, and suggest different avenues to unify both spaces for the purpose of in silico chemogenomics.
Removing rolling shutter distortion using optical flow and RANSAC

CMOS camera modules are used for smartphone. But CMOS camera modules have a problem of rolling shutter effect. In this paper, we propose an efficient method of removing the rolling shutter effect. We first compute the global motion vector by using the optical flow and the camera motion estimation algorithm. Then we estimate the velocity for each row of sensor array. Finally the distorted image is realigned. Experimental results show that the proposed method is more robust and faster than the previous method.
Structure of a rare non-standard sequence k-turn bound by L7Ae protein

Kt-23 from Thelohania solenopsae is a rare RNA kink turn (k-turn) where an adenine replaces the normal guanine at the 2n position. L7Ae is a member of a strongly conserved family of proteins that bind a range of k-turn structures in the ribosome, box C/D and H/ACA small nucleolar RNAs and U4 small nuclear RNA. We have solved the crystal structure of T. solenopsae Kt-23 RNA bound to Archeoglobus fulgidus L7Ae protein at a resolution of 2.95 Å. The protein binds in the major groove displayed on the outer face of the k-turn, in a manner similar to complexes with standard k-turn structures. The k-turn adopts a standard N3 class conformation, with a single hydrogen bond from A2b N6 to A2n N3. This contrasts with the structure of the same sequence located in the SAM-I riboswitch, where it adopts an N1 structure, showing the inherent plasticity of k-turn structure. This potentially can affect any tertiary interactions in which the RNA participates.
OPTIMAL CLASSIFICATION IN SPARSE GAUSSIAN GRAPHIC MODEL

Consider a two-class classification problem where the number of features is much larger than the sample size. The features are masked by Gaussian noise with mean zero and covariance matrix Sigma, where the precision matrix Omega = Sigma(-1) is unknown but is presumably sparse. The useful features, also unknown, are sparse and each contributes weakly (i.e., rare and weak) to the classification decision. By obtaining a reasonably good estimate of Omega, we formulate the setting as a linear regression model. We propose a two-stage classification method where we first select features by the method of Innovated Thresholding (IT), and then use the retained features and Fisher's LDA for classification. In this approach, a crucial problem is how to set the threshold of IT. We approach this problem by adapting the recent innovation of Higher Criticism Thresholding (HCT). We find that when useful features are rare and weak, the limiting behavior of HCT is essentially just as good as the limiting behavior of ideal threshold, the threshold one would choose if the underlying distribution of the signals is known (if only). Somewhat surprisingly, when Omega is sufficiently sparse, its off-diagonal coordinates usually do not have a major influence over the classification decision. Compared to recent work in the case where Omega is the identity matrix [Proc. Natl. Acad. Sci. USA 105 (2008) 14790-14795; Philos. Trans. R. Soc. Lond. Ser. A Math. Phys. Eng. Sci. 367 (2009) 4449-4470], the current setting is much more general, which needs a new approach and much more sophisticated analysis. One key component of the analysis is the intimate relationship between HCT and Fisher's separation. Another key component is the tight large-deviation bounds for empirical processes for data with unconventional correlation structures, where graph theory on vertex coloring plays an important role.
Improvisation in Product Innovation: The Contingent Role of Market Information Sources and Memory Types

Though improvisation has emerged as a crucial organizational competence, research wrestles with a key question – how can organizations benefit from improvisation? To advance research, I build a richer conceptualization of the role of knowledge resources – market information sources and memory types – in improvisation. I argue that as (a) internal and external sources of market information differ in speed and novelty and (b) procedural and declarative memory differ in articulation and abstractness, they shape the impact of improvisation on new product outcomes in a distinct way. A longitudinal survey of new products in the Dutch food industry uncovers that, contrary to prior thinking, improvisation increases cost efficiency when new product teams rely on internal market information and declarative memory and they minimize external market information. Though both sources of market information and low procedural memory weaken the negative impact of improvisation on market effectiveness, these conditions were not enough to make its impact positive, echoing traditional concerns with improvisation.
A comparative history of earnings management literature from Italy and the US

Using the comparative international accounting history approach advocated by Carnegie and Napier (2002), this study compares US and Italian earnings management (EM) literature published in the second half of the twentieth century and identifies the main similarities and differences in the research topics and methodologies. The historical comparison finds that although Italian and US contributions to EM literature grew in notably different contexts and research settings, they both recognized the issue of EM, agreed on its origins and shared some research topics. However, the two bodies of literature differed in respect of the research topics addressed and research methodologies adopted to analyse the EM issue. The discussion of these results provides also initial evidence of areas of potential contribution to the international debate on EM through cross-fertilization. The analysis demonstrates the fundamental role of comparative international accounting history in uncovering the potential contributions of national literatures to the development of accounting research at a genuinely international level. It also contributes to EM literature by bringing to international attention fifty years of Italian EM research that was previously unknown beyond Italian borders.
Futuring Digital Health and Wellness

The growing of ageing population worldwide and the need to concentrate research efforts on a specific target group motivate our research and focus on frail ageing people with chronic disease and physical/cognitive deficiencies. The primary goal is to maintain frail and dependant people in their own home and delay as much as possible their placement in a nursing home, through reliable assistive technologies, to maximize their physical and mental function, and to continue to engage in social networks with the community, so that they can continue to lead an independent and purposeful life. Today, providing assistive services for frail and dependant people could be done following two ways: the first axis consists on seeking assistive technologies dedicated not only to end-users, but also, and even mainly, to helper around the user (relatives, neighbours, caregivers,.) to supervise Activities of Daily Living (ADL). The second axis could be to concentrate on rehabilitation and coaching solutions targeting people with chronic disease (ex. diabetes type 2) helping them modify their lifestyle to manage their health conditions. Such systems focus mainly on developing serious games deployable at home and connected to regional or national health information systems (e.g. the shared medical file database in France). Consequently, in both options, the development cost is high, and this is also the reason that most smart home projects are still at the research lab level worldwide. There are efforts trying to transfer the research lab demonstration prototypes into homes or nursing homes, but migrating systems from a well controlled research lab environment into a much more complex real-world environment introduces tremendous challenges in terms of correctness, reliability and fault-tolerant requirements. Our objective is to promote demonstration guidelines and lessons learned in order to reach this goal. The presented work focuses on the quality of life of ageing people having cognitive and functional limitations, combined with diabetes type 2, and on recent achievements realised in France and Singapore.
Efficient Sideband Suppression in 4-D Antenna Arrays Through Multiple Time Modulation Frequencies

A novel approach, named multiple time modulation frequency, is proposed for the effective suppression of the sideband radiations in 4-D antenna arrays. The time modulation frequency, different for each array element, is exploited as additional design parameter to avoid the superposition of the sideband frequencies generated by the array elements. A customized optimization strategy including the analysis of the mutual coupling effects among the array elements is proposed for the 4-D array synthesis. Selected numerical and experimental results are provided to show that the sideband level of a 4-D antenna array can be significantly reduced by properly designing the switch-on time intervals of each element, even with uniform amplitude excitations.
Harnessing Immune Responses in the Tumor Microenvironment: All Signals Needed

An agonist CD40 monoclonal antibody (CP-870,893), in combination with gemcitabine, is well tolerated in patients with advanced pancreatic adenocarcinoma. The combination results in induction of cytokines, B cell activation, and clinical responses. These findings support testing of immunotherapies in combination with other established and targeted therapies. Clin Cancer Res; 19(22); 6061–3. ©2013 AACR.
Modelling, interlinking and discovering capabilities

Even though the concept of capability is an important element in service oriented architectures and enterprise information systems, little effort has been put towards modelling it as a first class citizen. Major related contributions were part of other efforts such as modelling business processes, service description and search requests. In case of service descriptions, current approaches confuse capabilities with invocation interfaces or do not go beyond the classical IOPEs paradigm. Both approaches do not allow to determine intuitively what the service does. In our work, we are interested in modelling and managing capabilities as stand alone entities, presented via an action verb and a set of domain related attributes. Presenting capabilities as such allows us to represent them at different levels of abstraction and make explicit links between them. These links permit to create a direct acyclic graph. Given this graph, we provide in this paper a heuristic approach for capability discovery. We also present the needed algorithms for building and maintaining such structure.
Relationship between the Components of Emotional Intelligence and Internet Addiction of Students in Kharazmi University

Internet is regarded as a largely pro-social, interactive, and information-driven medium and its use has skyrocketed and affected everyone's life, specifically, adolescents and young adults, a generation for whom the line between online and real world interaction is practically non-existent and the existence of addictive internet use may exert detrimental effects on their lives. One of the affecting factors of Internet addiction is the level of emotional intelligence. Therefore, the research purpose is to assess the relationship between the adolescents' emotional intelligence and Internet addiction disorder (IAD). Hence, the research employed a descriptive, correlative method and the sample comprised 400 students who were selected using stratified sampling form all the faculties located in Kharazmi University. The research tools included Internet Addiction test (IAT) designed and developed by Young and The Schutte Self-Report Emotional Intelligence Test (SSEIT). Results indicated that Internet addiction is significantly, negatively correlated to internet addiction. Moreover, results of multivariate regression indicated that appraisal of others' emotions explains 10.9% of the total variance. With regard to the disastrous effects of internet addiction, especially during adolescent and young adulthood, and the role of emotional intelligence as the predictor of internet addiction, coherent and effective policies should be formulated and developed for those at risk.
A pr 2 00 8 U-duality Invariant Dyon Spectrum in type II on T 6 Ashoke

We give a manifestly U-duality invariant formula for the degeneracy of 1/8 BPS dyons in type II string theory on T 6 for a U-duality invariant subset of charge vectors. Besides depending on the Cremmer-Julia invariant the degeneracy also depends on other discrete invariants of E 7(7) (Z Z).
Voluntary Emotion Suppression Modifies Psychophysiological Responses to Films

A fundamental aspect of successful social interaction is the fact people do not always experience or express emotions to their fullest extent but instead control them in a context-dependent manner. Emotion regulation involves the manipulation of subjective experience, behavior, and physiology. Previous researches have studied autonomic nervous system (ANS) responses during emotion regulation using only positive and negative stimuli without distinguishing between emotions, or it has focused on one specific emotion. Given the differences of ANS reactions to different categories of emotional stimuli, our study aims at comparing the physiological activity during emotion attending and emotion suppression using specific and distinct categories of emotions. Fifty subjects were presented with five films, inducing one of five emotions: happiness, sadness, fear, peacefulness, and disgust. While viewing the films, participants were instructed to perform an attending and a suppression task. We evaluated the following.
A component-based C++ framework for developing BDI agents

This paper presents a component-based framework for Belief, Desire, and Intention (BDI) agent programming in C++ that takes advantage of object orientation and provides a platform for agent development on a vast range of hardware, spanning from low-power single chip embeddable systems to high-performance grid computers. The framework is C++ standards conformant and supports debugging using tools provided by any standard IDE on virtually any operating-system platform.
Robust image representation and decomposition by Laplacian regularized latent low-rank representation

This paper discusses the image representation and decomposition problem using enhanced low-rank representation. Technically, we propose a Regularized Low-Rank Representation framework referred to as rLRR that is motivated by the fact that Latent Low-Rank Representation (LatLRR) delivers robust and promising results for image representation and feature extraction through recovering the hidden effects, but the locality among both similar principal and salient features to be encoded are not preserved in the original LatLRR formulation. To address this problem for obtaining enhanced performance, rLRR is proposed through incorporating an appropriate Laplacian regularization term that allows us to keep the local geometry of close features. Similar to LatLRR, rLRR decomposes a given data matrix from two directions by calculating a pair of low-rank matrices. But the similarities among principal features and salient features can be clearly preserved by rLRR. Thus the correlated features can be well grouped and the robustness of representations can also be effectively improved. The effectiveness of rLRR is examined by representation and recognition of real images. Results verified the validity of our presented rLRR technique.
Copper Nanoparticles as Potential Antimicrobial Agent in Disinfecting Root Canals. A Systematic Review

Copper was registered as the first solid antimicrobial material. Its availability makes it an important option as an antibacterial agent. At nanoparticle size it does not exceed 100 nm, allowing close interaction with microbial membranes, enhancing its effect even more. Copper generates toxic hydroxyl radicals that damage cell membranes of Gram-negative and Gram-positive bacteria, among the latter, Enterococcus faecalis, which are present in infected radicular canals. Synthesis of metal nanoparticles with antimicrobial properties has become a viable alternative and has promising applications in the fight against pathogenic microorganisms. Furthermore, the use of some polymers to stabilize nanoparticles increases their release time and may as well decrease the risk of bacterial recolonization and biofilm formation within the ducts, enhancing the antimicrobial properties of these compounds.The aim of this article is to conduct a systematic review of the literature on antimicrobial copper nanoparticles, their current applications and their potential use in the area of oral health, specifically in the field of endodontics.
NCSTRL: Design and deployment of a globally distributed digital library

The World Wide Web provides unprecedented access to globally distributed content. The extent and uniform accessibility of the Web has proven beneficial for research, education, commerce, entertainment, and numerous other uses. Ironically, the fact that the Web is an information space without boundaries has also proven its biggest flaw. Key aspects of libraries, such as selectivity of content, customization of tools and services relative to collection and patron characteristics, and management of content and services are noticeably absent. Over the past four years, we researched the technology and deployment of a digital library architecture that makes it possible to create managed information spaces, digital libraries, within the World Wide Web. Our work has taken place in the context of NCSTRL,1a digital library of computer science research reports. The technical foundation of NCSTRL is Dienst, a protocol and architecture for distributed digital libraries that we developed as part of the DARPA‐funded Computer Science Technical Reports Project. At the time of the writing of this paper, the NCSTRL collection consisted of papers from more than 100 research institutions residing in servers distributed across the United States, Europe, and Asia. In addition, the Dienst protocol and implementation has been successfully adopted by a number of other distributed collections. In this paper, we review our experiences with NCSTRL and Dienst, describe some of the lessons we have learned from the deployment experience, and define some directions for the future.
The Regulation of Trypanosome Gene Expression by RNA-Binding Proteins

The genome organization of trypanosomes, leishmanias, and related kinetoplastid organisms is highly unusual: Each RNA polymerase II promoter precedes multiple open reading frames, and the primary transcript is cut into individual mRNAs by 59 trans splicing and 39 polyadenylation [1]. Dedicated control of transcription at the level of individual mRNAs is therefore not possible. Nevertheless, mRNA levels are highly controlled: Although some gene sequences are represented by several hundred mRNAs, most mRNAs are present at just one or two copies per cell [2]. Constitutively high mRNA levels can be obtained by having many identical genes, but for most genes, more flexible control points are used: mRNA processing, export from the nucleus, translation, and mRNA decay. Kinetoplastid mRNAs are probably bound by multiple proteins possessing varying degrees of sequence specificity. The poly(A) tail is masked by poly(A) binding proteins (PABP1 and 2). During translation the 59 cap is bound by initiation factors [3,4]; it is expected that, as in other eukaryotes, these interact with PABP, increasing translation efficiency and shielding the mRNA from degradation. Multiple other proteins could bind both translated and untranslated regions, with potential competition between proteins for particular binding sites. Interactions between RNAbinding proteins and proteins of the processing, translation, and degradation machineries will combine to determine RNA fate. This review focuses on Trypanosoma brucei. T. brucei has two lifecycle stages that grow in culture in the laboratory: the bloodstream form (similar to that in mammalian blood) and the procyclic form (similar to that in the midgut of Tsetse flies). Differentiation of bloodstream forms to procyclics occurs via an intermediate, nondividing stage, the stumpy form. In Tsetse, the procyclic form in the midgut differentiates to epimastigotes, then to mammalianinfective metacyclic forms in the salivary glands. Methods used for the investigation of RNA-binding proteins are listed in Table 1.