Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Multimodal Communication on Persuasiveness and Perceived Politeness of Virtual Agents in Small Groups

Multimodal communication is essential in human interactions, as it allows for a more comprehensive and nuanced exchange of information and emotions. The use of multiple communication channels such as speech, body language, and gaze can enhance the clarity and richness of the communication, leading to better understanding and more effective social interactions. This paper investigates the importance of multimodal expressive communication, specifically voice, arm gestures, and gaze, in regulating human-agent interaction when joining a group of two virtual agents in a virtual reality environment. One of the virtual agents in the group uses politeness behaviors based on Brown and Levinson's politeness theory to invite participants to join the group at the side further to them, even though a closer side is available. The study finds that a combination of all modalities (verbal, gaze, arm gesture) is more effective in persuading participants to join the group at the farthest side, and arm gestures alone are more effective than gaze behavior although they are perceived to be less polite. Furthermore, although verbal-only communication can be as persuasive as other modalities, it can place a greater cognitive load on participants. This increased cognitive load may lead to delayed responses in comparison to other modalities. The findings give insight to designers of human-agent interaction systems about the use of multiple communication channels, particularly nonverbal behaviors such as arm gestures, to enhance the effectiveness of persuasive communication but they also need to balance this with other factors such as the impression and perceived politeness of virtual agents.
Effects of Agent's Embodiment in Human-Agent Negotiations

Human-agent negotiation has recently attracted researchers' attention due to its complex nature and potential usage in daily life scenarios. While designing intelligent negotiating agents, they mainly focus on the interaction protocol (i.e., what to exchange and how) and strategy (i.e., how to generate offers and when to accept). Apart from these components, the embodiment may implicitly influence the negotiation process and outcome. The perception of a physically embodied agent might differ from the virtually embodied one; thus, it might influence human negotiators' decisions and responses. Accordingly, this work empirically studies the effect of physical and virtual embodiment in human-agent negotiations. We designed and conducted experiments where human participants negotiate with a humanoid robot in one setting, whereas they negotiate with a virtually embodied replica of that robot in another setting. The experimental results showed that social welfare was statistically significantly higher when the negotiation was held with a virtually embodied robot rather than a physical robot. Human participants took the negotiation more seriously against physically embodied agents and made more collaborative moves in the virtual setting. Furthermore, their survey responses indicate that participants perceived our robot as more humanlike when it is physically embodied.
Semantic Object-based Human-like Semantic Map Construction

The autonomous movement of robots relies on map support. The traditional SLAM systems, based on low-level features, require a large amount of data to build maps. In contrast, humans can describe environmental information using concise semantic symbols. In this work, we propose a novel method for constructing an abstract semantic map by leveraging the pattern of human memory of the environment. Several kinds of objects are designated as semantic landmarks from the environment, whose spatial coordinates are obtained by multi-view observation information to form semantic points for robot self-localization. A laser sensor is used to obtain obstacle point clouds in the environment, which are abstracted into semantic line segments for constraining robot movement. The combination of semantic points and semantic line segments forms the proposed semantic map. Finally, we evaluate the feasibility of our method in a real-world environment.
Research on Information Strategy of Social Media Short Video Marketing Co-creation Based on Data Mining

In the new media era, short video co-creation has become an important measure for enterprise Internet marketing. This paper takes real short video marketing co-creation activities as a case, uses network crawler, natural language analysis, machine learning, statistical methods and other data mining methods to analyze the influence of different information types of short video producers and short video content on marketing effect (like,comment,share). It is found that the number of fans positively affects the marketing effect, the marketing effect of short video released by marketing personnel and terminal shop owners is better, the number of likes of emotional short videos is higher than that of advertising, the number of likes and shares of positive short videos is higher than that of neutral short videos. Finally, it is proposed that enterprises should not blindly pursue flow rate when carrying out short video marketing co-creation, but pay attention to and support the marketing co-creation groups with high relevance and high trust with the enterprise, the content of short video should meet the emotional and social needs of users, and spread positive and conform to the enterprise brand image information.
Eecient Searching with Linear Constraints

We show how to preprocess a set S of points in R into an external memory data structure that e ciently supports linear-constraint queries. Each query is in the form of a linear constraint a x b; the data structure must report all the points of S that satisfy the constraint. Our goal is to minimize the number of disk blocks required to store the data structure and the number of disk accesses (I/Os) required to answer a query. For d = 2, we present the rst near-linear size data structure that can answer linear-constraint queries using an optimal number of I/Os. We also present a linearsize data structure that can answer queries e ciently in the worst case. We combine these two approaches to obtain tradeo s between space and query time. Finally, we show that some of our techniques extend to higher dimensions. Center for Geometric Computing, Department of Computer Science, Duke University, Box 90129, Durham, NC 27708{0129; fpankaj,large,je e,jsvg@cs:duke:edu; http://www:cs:duke:edu/ fpankaj,large,je e,jsvg. Supported in part by National Science Foundation research grant CCR{93{01259, by Army Research O ce MURI grant DAAH04{96{1{0013, by a Sloan fellowship, by a National Science Foundation NYI award and matching funds from Xerox Corporation, and by a grant from the U.S.-Israeli Binational Science Foundation. Supported in part by U.S. Army Research O ce MURI grant DAAH04{96{1{0013. Supported in part by National Science Foundation grant DMS{9627683 and by U.S. Army Research O ce MURI grant DAAH04{96{1{0013. Dipartimento di Informatica e Sistemistica, Universit a di Roma \La Sapienza," Via Salaria 113, 00198, Rome; pgf@dis:uniroma1:it; http://www-ae:dis:uniroma1:it/ae/people/ franciosa/. Supported in part by EU Project no. 20244 (AlcomIT). Part of this work was done while visiting Duke University under the Short Term Mobility program of CNR. Supported in part by U.S. Army Research O ce MURI grant DAAH04{96{1{0013 and by National Science Foundation grant CCR{9522047.
Eecient Searching with Linear Constraints

We show how to preprocess a set S of points in R d into an external memory data structure that eeciently supports linear-constraint queries. Each query is in the form of a linear constraint a x b; the data structure must report all the points of S that satisfy the constraint. Our goal is to minimize the number of disk blocks required to store the data structure and the number of disk accesses (I/Os) required to answer a query. For d = 2, we present the rst near-linear size data structure that can answer linear-constraint queries using an optimal number of I/Os. We also present a linear-size data structure that can answer queries eeciently in the worst case. We combine these two approaches to obtain tradeoos between space and query time. Finally, we show that some of our techniques extend to higher dimensions.
A Condensed Representation to Find Frequent Patterns

Given a large set of data, a common data mining problem is to extract the frequent patterns occurring in this set. The idea presented in this paper is to extract a condensed representation of the frequent patterns called disjunction-free sets, instead of extracting the whole frequent pattern collection. We show that this condensed representation can be used to regenerate all frequent patterns and their exact frequencies. Moreover, this regeneration can be performed without any access to the original data. Practical experiments show that this representation can be extracted very eÆciently even in diÆcult cases. We compared it with another representation of frequent patterns previously investigated in the literature called frequent closed sets. In nearly all experiments we have run, the disjunction-free sets have been extracted much more eÆciently than frequent closed sets.
Indexing for data models with constraints and classes (extended abstract)

We examine I/O-efficient data structures that provide indexing support for new data models. The database languages of these models include concepts from constraint programming (e.g., relational tuples are generalized to conjunctions of constraints) and from object-oriented programming (e.g., objects are organized in class hierarchies). Let n be the size of the database, c the number of classes, B the secondary storage page size, and t the size of the output of a query. Indexing by one attribute in the constraint data model (for a fairly general type of constraints) is equivalent to external dynamic interval management, which is a special case of external dynamic 2-dimensional range searching. We present a semi-dynamic data structure for this problem which has optimal worst-case space O(n/B) pages and optimal query I/O time O(logBn+t/B) and has O(logBn+(log2Bn)/B) amortized insert I/O time. If the order of the insertions is random then the expected number of I/O operations needed to perform insertions is reduced to O(logBn). Indexing by one attribute and by class name in an object-oriented model, where objects are organized as a forest hierarchy of classes, is also a special case of external dynamic 2-dimensional range searching. Based on this observation we first identify a simple algorithm with good worst-case performance for the class indexing problem. Using the forest structure of the class hierarchy and techniques from the constraint indexing problem, we improve its query I/O time from O(log2c logBn + t/B) to O(logB + log2B).
Improved Load Balancing Algorithm Based on Long Short-Term Memory Networks

User request processing in Web clusters is often assigned to some nodes with network congestion, so that the cluster effect cannot be shown as expected. A dynamic load balancing improvement scheme is proposed based on Long Short-Term Memory (LSTM) neural network. The scheme combines the performance of server nodes and real-time comprehensive load information to adjust the load weights, which makes the allocation of preprocessing nodes more reasonable, and then predicts the network conditions of preprocessing nodes with the help of LSTM algorithm, so as to avoid that the requests are allocated to some nodes with poor network quality. Compared with the traditional scheme, the proposed dynamic load improvement scheme can effectively improve the load effect, the average response time of the cluster is reduced by 39%, and the throughput is also improved by 24%.
Optimized mucin-selective enrichment strategy to probe the mucinome

Mucin-domain glycoproteins are densely O-glycosylated and play critical roles in a host of healthy and diseasedriven biological functions. Previously, we developed a mucin-selective enrichment strategy by employing a catalytically inactive mucinase (StcE) conjugated to solid support. While this method was effective, it suffered from low throughput and high sample requirements. Further, the elution step required boiling in SDS, thus necessitating an in-gel digest with trypsin. Here, we optimized our previous enrichment method to include elution conditions amenable to mucinase digestion and downstream analysis with mass spectrometry. This increased throughput and lowered sample input while maintaining mucin selectivity and enhancing glycopeptide signal. We then benchmarked this technique against different O-glycan binding moieties for their ability to enrich mucins from various cell lines and human serum. Overall, the new method outperformed our previous procedure and all other enrichment techniques tested. This allowed for effective isolation of more mucin-domain glycoproteins, resulting in a high number of O-glycopeptides, thus enhancing our ability to analyze the mucinome.
Synthesis of Zeolite Na-LSX from Iraqi Natural Kaolin using Alkaline Fusion Prior to Hydrothermal Synthesis Technique

The synthesis of zeolite materials by hydrothermal transformation of kaolin using an alkaline fusion prior to hydrothermal synthesis method was investigated. The kaolin clay used in the present investigation was supplied from Iraq. The physical and chemical characterization of the starting kaolin and produced zeolite Na-LSX samples were carried out using different analytical techniques such as Scanning Electron Microscopy (SEM), Energy Dispersive Spectroscopy (EDS), X – Ray Diffraction (XRD), X – Ray Fluorescence (XRF), Thermogravimetric Analysis (TGA), Fourier Transform Infrared (FT-IR) Spectroscopy and Inductively Coupled Plasma-Optical Emission Spectrometer (ICP-OES). An alkaline fusion method was introduced prior to the hydrothermal treatment while kaolin clay powder was mixed manually with NaOH powder (ratio = 1/1.2 in weight). The metakaolinisation phase was achieved by calcining the mixture in air at 600 oC for 1hr. The result from this route shows that zeolite Na-LSX with cubic rounded edge crystal habit have been successfully synthesised. Finally, The kinetic study indicated the suitability of the zeolite Na-LSX for the removal of Cu2+, Fe3+, Pb2+ and Zn2+ ions from synthetic wastewater.
A hyperparameter-randomized ensemble approach for robust clustering across diverse datasets

Clustering analysis is widely used to group objects by similarity, but for complex datasets such as those produced by single-cell analysis, the currently available clustering methods are limited by accuracy, robustness, ease of use, and interpretability. To address these limitations, we developed an ensemble clustering method with hyperparameter randomization that outperforms other methods across a broad range of single-cell and synthetic datasets, without the need for manual hyperparameter selection. In addition to hard cluster labels, it also outputs soft cluster memberships to characterize continuum-like regions and per cell overlap scores to quantify the uncertainty in cluster assignment. We demonstrate the improved clustering interpretability from these features by tracing the intermediate stages between handwritten digits in the MNIST dataset, and between tanycyte subpopulations in the hypothalamus. This approach improves the quality of clustering and subsequent downstream analyses for single-cell datasets, and may also prove useful in other fields of data analysis.
Cloud-Edge Collaborative Task Scheduling Optimization Algorithm in Mobile Edge

In edge computing, decision-making for task execution on edge devices with limited resources can significantly improve offloading efficiency and reduce application processing latency. Aiming at the offloading decision-making problem in the mobile edge computing environment, this paper proposes a network model and a task scheduling model to define the associated edge devices, collaborative edge devices, and cloud task execution. Meanwhile, we develop a joint optimization algorithm to obtain the optimal task scheduling solution associated under the task execution delay constraint. The simulation results highlight that the proposed joint optimization algorithm is faster to execute than other strategies and effectively adapts to large-scale task scheduling.
Where Do They Go?: Overhearing Conversing Pedestrian Groups during Scene Exploration

On entering an unknown immersive virtual environment, a user's first task is gaining knowledge about the respective scene, termed scene exploration. While many techniques for aided scene exploration exist, such as virtual guides, or maps, unaided wayfinding through pedestrians-as-cues is still in its infancy. We contribute to this research by indirectly guiding users through pedestrian groups conversing about their target location. A user who overhears the conversation without being a direct addressee can consciously decide whether to follow the group to reach an unseen point of interest. We outline our approach and give insights into the results of a first feasibility study in which we compared our new approach to non-talkative groups and groups conversing about random topics.
Impossibility of distributed consensus with one faulty process

The consensus problem involves an asynchronous system of processes, some of which may be unreliable. The problem is for the reliable processes to agree on a binary value. We show that every protocol for this problem has the possibility of nontermination, even with only one faulty process. By way of contrast, solutions are known for the synchronous case, the "Byzantine Generals" problem.
Towards an Existential Types Model for Java Wildcards

Wildcards extend Java generics by softening the mismatch between subtype and parametric polymorphism. Although they are a key part of the Java 5.0 programming language, a type system including wildcards has never been proven type sound. Wildcards have previously been formalised as existential types. In this paper we extend FGJ, a featherweight formalisation of Java with generics, with existential types. We prove that this calculus, ∃J, is type sound, and illustrate how it models wildcards in the Java Programming Language. ∃J is not a full model for Java wildcards, because it does not support lower bounds for wildcards. We discuss why ∃J can not be easily extended with lower bounds, and how full Java wildcards could be modelled in a type sound way.
Proceedings of the NIPS 2005 Workshop on Machine Learning for Implicit Feedback and User Modeling Workshop at NIPS 2005

Eyetools was born in 2000 out of the Stanford University Advanced Eye Interpretation Project. After seeing the business value of eyetracking resulting from the Stanford-Poynter Project, a collaborative study between the Poynter Institute and Stanford University’s Department of Communications around the viewing of online news sites, founder Greg Edwards spun out Eyetools. Since then, Eyetools’ pioneering work in inferring mental state from eye movements and visualizing eyetracking data has led to several key patents in the area, and has enabled eyetracking to be put into use more easily by an ever expanding number of companies and people. Eyetools’ roots in Human-Computer Interaction began in 1995 ∗PASCAL Invited Talk
Learning the rules of the game: The role of generic "you" and "we" in shaping children's interpretations of norms.

A critical skill of childhood is learning social norms. We examine whether the generic pronouns "you" and "we," which frame information as applying to people in general rather than to a specific individual, facilitate this process. In one pre-registered experiment conducted online between 2020 and 2021, children 4- to 9-year-old primarily living in the midwestern U.S. (N = 146, 75 girls, 71 boys, Mage = 7.14, SD = 1.69, 82% White) interpreted actions described with generic pronouns (vs. "I") as normatively correct and selected the speaker who used generic pronouns as the rule-follower, particularly when generic pronouns were presented first. There were no significant effects of age. These results illustrate how generic pronouns influence how children discern unfamiliar norms and form interpersonal judgments.
Evaluation of electrochemiluminescence immunoassays for immunosuppressive drugs on the Roche cobas e411 analyzer [version 1; peer review: 2 approved]

Background: Therapeutic drug monitoring of immunosuppressant drugs are used to monitor drug efficacy and toxicity and to prevent organ transplantation rejection. This study evaluates the analytical performance of semi-automated electrochemiluminescence immunoassays (ECLIA) for cyclosporine (CSA), tacrolimus (TAC) and sirolimus (SRL) on the Roche cobas e 411 analyzer at a major transplant hospital to identify method suitability and limitations. Methods: Residual whole blood samples from patients undergoing immunosuppressant therapy were used for evaluation. Experiments included imprecision, linearity, functional sensitivity, method comparisons and lot-to-lot assessments. Results: Total imprecision ranged from 3.3 to 7.1% for CSA,
Bibliometric Study on Quality Journalism in the Scopus Database: Evolution of the Topic and Characteristics

This article uses a term search to describe how academic work on the relationship be-tween journalism and quality has evolved. It relies on a bibliometric study and content analysis of the Scopus database. Using the VOSviewer tool, this article presents automated analyses of the Scopus system and network maps that pertain to article terms. The goal is to outline scientific production’s features and the impact of research on quality journalism identifying emerging trends in this research area. The study sample consists of 971 research articles published be-tween 1939 and 2022, specifically focusing on social sciences articles across various languages, indexed in Scopus. The findings suggest a rising interest in journalism quality within analysed scientific journals, especially in the 21st century, predominantly in Western countries, despite a growing trend in Eastern countries. The United States is the primary source for articles, citations, and first authors. Additionally, the three journals publishing most on journalism quality are of Anglo-Saxon origin. Research clusters are developed on the object of study outside this axis, led by Spanish and Portuguese scientific production. The bibliometric analysis also shows the evolution of topics related to journalism quality.