La Rueda del Tiempo es una ficción serializada producida por Prime Video que, aunque retoma el tradicional monomito propio de la fantasía épica, sitúa en un lugar central a las mujeres y, más concretamente, al uso que estas hacen del poder. Este artículo tiene por objeto examinar los tipos de estructuras sociales que se representan en la serie: la matriarcal, la matrilineal, la patriarcal y aquella que esclaviza a las mujeres. Se analizarán seis tipos de feminidad que se plasman a lo largo de la narrativa: comunitaria, espiritual, hembrista, revolucionaria, sacerdotal y tradicional. El trabajo adopta una metodología propia de los estudios culturales, a partir de la visualización y exégesis de los episodios que conforman esta producción audiovisual. Las conclusiones alcanzadas ponen de manifiesto que esta saga no sólo reinventa el arquetipo de la feminidad en el género fantástico, sino que también explora el conflicto de clases.
The transition of Large Language Models (LLMs) from exploratory tools to active "silicon subjects" in social science lacks extensive validation of operational validity. This study introduces Conditioned Comment Prediction (CCP), a task in which a model predicts how a user would comment on a given stimulus by comparing generated outputs with authentic digital traces. This framework enables a rigorous evaluation of current LLM capabilities with respect to the simulation of social media user behavior. We evaluated open-weight 8B models (Llama3.1, Qwen3, Ministral) in English, German, and Luxembourgish language scenarios. By systematically comparing prompting strategies (explicit vs. implicit) and the impact of Supervised Fine-Tuning (SFT), we identify a critical form vs. content decoupling in low-resource settings: while SFT aligns the surface structure of the text output (length and syntax), it degrades semantic grounding. Furthermore, we demonstrate that explicit conditioning (generated biographies) becomes redundant under fine-tuning, as models successfully perform latent inference directly from behavioral histories. Our findings challenge current "naive prompting" paradigms and offer operational guidelines prioritizing authentic behavioral traces over descriptive personas for high-fidelity simulation.
José Manuel Rúa-Estévez, Alicia Meleiro-Estévez, Pablo Fondo-Ferreiro
et al.
This work presents a simulator designed for the validation, evaluation, and demonstration of flying adhoc networks (FANETs) using 5G vehicle-to-everything (V2X) communications and the named-data networking (NDN) paradigm. The simulator integrates the ns-3 network simulator and the Zenoh NDN protocol, enabling realistic testing of applications that involve the multi-hop communication among multiple unmanned aerial vehicles (UAVs).
The history of publishing in Poland encompasses many issues associated with the emergence and dissemination of printed books. Of fundamental significance to the study of these issues are the records of the publishing output: while we have nearly complete, though still underexamined, records of this output for the period from the 15th to the 18th century, documented in bibliographies and catalogues, the situation is worse when it comes to the 19th and 20th centuries, until the outbreak of the Second World War. In this respect, what we need is not only a continuation, but a radical intensification of bibliographic work. This concerns works published in the Latin, Cyrillic, Hebrew and Greek scripts, as well as musical notation. Polish book scholars have devoted a lot of attention to the beginnings of printing in Poland. The historiography concerning various typographic workshops located in the former Polish-Lithuanian Commonwealth is rich; however, it still requires further extensive studies. Scholars have also been interested in phenomena influ- encing the content structure of printed publications, such as publishing privileges (in the former Polish-Lithuanian Commonwealth), censorship and restrictions imposed by the partitioning powers and later by Poland’s communist authorities, as a result of which Polish publications had to be printed abroad and an independent publishing movement emerged. The scholars’ research interests have also focused on books as products of printers and publishers and on the publication of written works. Scholars have examined both the various components of the book (title page, printer’s signet, stemmata, etc.) and its editorial composition as a whole. Their undoubted achievements in the studies of the history of publishing in Poland are significant, yet in many areas they need to be continued and expanded (one important task is the edition of sources for the study of the history of Polish publishing) and to investigate the phenomena that stem from developmental tendencies in modern book studies.
Bibliography. Library science. Information resources, Communication. Mass media
Prima Ayu Rizqy Mahanani, Fatma Dian Pratiwi, Fartika Ifriqia
et al.
This article tends to analyze how Muslim women's activists, who are the members of Nasyiatul Aisyiyah and Fatayat NU in Kediri and Yogyakarta, build their digital literacy to prevent violence in social media. Mainly due to the digital divide between men and women, which causes imbalance and injustice when they access digital media. The method used in data collection was semi-ethnographic, in which the researcher participated in observing research objects when carrying out activities using digital technology, interviews, and documentation on 3 members of Nasyiatul Aisyiyah and Fatayat NU, both in Jogja and Kediri. The research findings show that what has been stigmatized to women so far is that they are powerless to master information and communication technology, which does not apply to members of Fatayat NU and Nasyiatul Aisyiyah. This research shows that women are also reliable in accessing the internet for the benefit of empowering women, especially KBGO issues. This research has provided a different understanding of the phenomenon of the massive use of internet-based technology by female activists
DRHBc Mass Table Collaboration, Peng Guo, Xiaojie Cao
et al.
The mass table in the deformed relativistic Hartree-Bogoliubov theory in continuum (DRHBc) with the PC-PK1 density functional has been established for even-$Z$ nuclei with $8\le Z\le120$, extended from the previous work for even-even nuclei [Zhang $\it{et.~al.}$ (DRHBc Mass Table Collaboration), At. Data Nucl. Data Tables 144, 101488 (2022)]. The calculated binding energies, two-nucleon and one-neutron separation energies, root-mean-square (rms) radii of neutron, proton, matter, and charge distributions, quadrupole deformations, and neutron and proton Fermi surfaces are tabulated and compared with available experimental data. A total of 4829 even-$Z$ nuclei are predicted to be bound, with an rms deviation of 1.477 MeV from the 1244 mass data. Good agreement with the available experimental odd-even mass differences, $α$ decay energies, and charge radii is also achieved. The description accuracy for nuclear masses and nucleon separation energies as well as the prediction for drip lines is compared with the results obtained from other relativistic and nonrelativistic density functional. The comparison shows that the DRHBc theory with PC-PK1 provides an excellent microscopic description for the masses of even-$Z$ nuclei. The systematics of the nucleon separation energies, odd-even mass differences, pairing energies, two-nucleon gaps, $α$ decay energies, rms radii, quadrupole deformations, potential energy curves, neutron density distributions, and neutron mean-field potentials are discussed.
Jonathan A. Soares, Kayol S. Mayer, Dalton S. Arantes
In the ever-evolving field of digital communication systems, complex-valued neural networks (CVNNs) have become a cornerstone, delivering exceptional performance in tasks like equalization, channel estimation, beamforming, and decoding. Among the myriad of CVNN architectures, the phase-transmittance radial basis function neural network (PT-RBF) stands out, especially when operating in noisy environments such as 5G MIMO systems. Despite its capabilities, achieving convergence in multi-layered, multi-input, and multi-output PT-RBFs remains a daunting challenge. Addressing this gap, this paper presents a novel Deep PT-RBF parameter initialization technique. Through rigorous simulations conforming to 3GPP TS 38 standards, our method not only outperforms conventional initialization strategies like random, $K$-means, and constellation-based methods but is also the only approach to achieve successful convergence in deep PT-RBF architectures. These findings pave the way to more robust and efficient neural network deployments in complex digital communication systems.
Mohamed Bayan Kmainasi, Ali Ezzat Shahroor, Maram Hasanain
et al.
Large Language Models (LLMs) have demonstrated remarkable success as general-purpose task solvers across various fields. However, their capabilities remain limited when addressing domain-specific problems, particularly in downstream NLP tasks. Research has shown that models fine-tuned on instruction-based downstream NLP datasets outperform those that are not fine-tuned. While most efforts in this area have primarily focused on resource-rich languages like English and broad domains, little attention has been given to multilingual settings and specific domains. To address this gap, this study focuses on developing a specialized LLM, LlamaLens, for analyzing news and social media content in a multilingual context. To the best of our knowledge, this is the first attempt to tackle both domain specificity and multilinguality, with a particular focus on news and social media. Our experimental setup includes 18 tasks, represented by 52 datasets covering Arabic, English, and Hindi. We demonstrate that LlamaLens outperforms the current state-of-the-art (SOTA) on 23 testing sets, and achieves comparable performance on 8 sets. We make the models and resources publicly available for the research community (https://huggingface.co/collections/QCRI/llamalens-672f7e0604a0498c6a2f0fe9).
Social media popularity (SMP) prediction is a complex task involving multi-modal data integration. While pre-trained vision-language models (VLMs) like CLIP have been widely adopted for this task, their effectiveness in capturing the unique characteristics of social media content remains unexplored. This paper critically examines the applicability of CLIP-based features in SMP prediction, focusing on the overlooked phenomenon of semantic inconsistency between images and text in social media posts. Through extensive analysis, we demonstrate that this inconsistency increases with post popularity, challenging the conventional use of VLM features. We provide a comprehensive investigation of semantic inconsistency across different popularity intervals and analyze the impact of VLM feature adaptation on SMP tasks. Our experiments reveal that incorporating inconsistency measures and adapted text features significantly improves model performance, achieving an SRC of 0.729 and an MAE of 1.227. These findings not only enhance SMP prediction accuracy but also provide crucial insights for developing more targeted approaches in social media analysis.
The Management Information System, which includes Human Resources, Network, and Database, currently has a vital role in achieving the company's goals and sustainability. The information obtained will be processed into data and used for a company's decision-making. Companies engaged in the field of Media and Communication are also very closely related to the above variables, which help determine their company's sustainability. Therefore, it is necessary to understand Management Information Systems, especially Human Resources, Hardware, and Databases, to create effective, quality, and valuable information for the company. The purpose of writing this article is to describe the variables above. The results are: 1) The Role of Human Resources in Mass Media Companies, 2) Hardware in Mass Media Companies, 3) Databases in Mass Media Companies.
Ahmed S. Alahmed, Guido Cavraro, Andrey Bernstein
et al.
We propose an operating-envelope-aware, prosumer-centric, and efficient energy community that aggregates individual and shared community distributed energy resources and transacts with a regulated distribution system operator (DSO) under a generalized net energy metering tariff design. To ensure safe network operation, the DSO imposes dynamic export and import limits, known as dynamic operating envelopes, on end-users' revenue meters. Given the operating envelopes, we propose an incentive-aligned community pricing mechanism under which the decentralized optimization of community members' benefit implies the optimization of overall community welfare. The proposed pricing mechanism satisfies the cost-causation principle and ensures the stability of the energy community in a coalition game setting. Numerical examples provide insights into the characteristics of the proposed pricing mechanism and quantitative measures of its performance.
Tim Schreiter, Lucas Morillo-Mendez, Ravi T. Chadalavada
et al.
Robots are increasingly used in shared environments with humans, making effective communication a necessity for successful human-robot interaction. In our work, we study a crucial component: active communication of robot intent. Here, we present an anthropomorphic solution where a humanoid robot communicates the intent of its host robot acting as an "Anthropomorphic Robotic Mock Driver" (ARMoD). We evaluate this approach in two experiments in which participants work alongside a mobile robot on various tasks, while the ARMoD communicates a need for human attention, when required, or gives instructions to collaborate on a joint task. The experiments feature two interaction styles of the ARMoD: a verbal-only mode using only speech and a multimodal mode, additionally including robotic gaze and pointing gestures to support communication and register intent in space. Our results show that the multimodal interaction style, including head movements and eye gaze as well as pointing gestures, leads to more natural fixation behavior. Participants naturally identified and fixated longer on the areas relevant for intent communication, and reacted faster to instructions in collaborative tasks. Our research further indicates that the ARMoD intent communication improves engagement and social interaction with mobile robots in workplace settings.
This study has attempted to determine the role of mass s media interventions on promoting public health knowledge and behavioral social change against COVID-19 pandemic disease in Jordan. Based on communication theory and literature review in health communication, the study develops and examines four major hypotheses that link mass media channels, preferred message types and the senders of preferred message sources, the level of public health knowledge and behavioral social change against Corona virus pandemic disease in Jordan—based on demographic characteristics (gender, age, education, and territory location). To carry out this study; an online questionnaire was prepared and conducted in Jordan and a number of 2,555 social media platforms participants were reached. Content analysis method was mainly deployed for data analysis. The findings showed significant relationships between the preferred type of mass media channels (R = .47), preferred message types (R = .58), and preferred message sources (R = .56) and the level of public health knowledge and behavioral social change against COVID-19 pandemic in Jordan. The study also found that the preferred mass media channels, message types, and message sources differ among the respondents’ demographic characteristics (gender, age, and education). In contrast, no differences found attributed to territory locations.
Marked by both deep interconnectedness and polarization, the contemporary media system in the United States features news outlets and social media that are bound together, yet deeply divided along partisan lines. This article formally analyzes communication flows surrounding mass shootings in the hybrid and polarized U.S. media system. We begin by integrating media system literature with agenda setting and news framing theories and then conduct automated text analysis and time series modeling. After accounting for exogenous event characteristics, results show that (a) sympathy and gun control discourses on Twitter preceded news framing of gun policy more than the other way around, and (b) conservatives on Twitter and conservative media reacted to progressive discourse on Twitter, without their progressive counterparts exhibiting a similar reactiveness. Such results shed light on the influence of social media on political communication flows and confirm an asymmetry in the ways partisan media ecosystems respond to social events.
Fábio Tonissi Moroni, Raquel Borges-Moroni, Eduardo Loebel
et al.
Instalações animais são locais onde ocorre reprodução, manutenção ou experimentação em seres vivos para atividades de ensino e pesquisa. Atualmente, elas são legalizadas. Mesmo assim, isso não é suficiente para convencer alguns setores da sociedade civil sobre a necessidade da existência desses espaços. Portanto, para preservar a boa reputação das universidades, é justificável fortalecer a comunicação interna. Logo, este trabalho propõe etapas para a construção desse plano de comunicação. Como resultado, sugerem-se sete passos, os quais são discutidos sob a ótica das teorias institucionais.
Rusijos karas prieš Ukrainą suaktualina putiniškojo režimo propagandos „argumentų“, neva pagrindžiančių agresiją prieš suverenią valstybę, istorinės logikos ir socioideologinės semantikos tyrimus. Straipsnyje lyginamos XIX a. Rusijos inteligentų ‒ slavofilų ir dešiniųjų narodnikų (liaudininkų) bei XXI a. 1–3 dešimtmečių putiniškojo režimo propagandoje eksploatuojamos liaudiškumo sampratos, veikiančios kaip mitologemų ir ideologemų rinkinys. Keliamas slavofilų ir dešiniųjų narodnikų ideologijos istorinio ir politinio perimamumo klausimas putiniškojo režimo propagandoje, vykdomoje įvairiuose karo Ukrainoje kontekstuose. Tyrime išryškinama dviprasmybė ‒ viena vertus, nekorektiška tiesiogiai kildinti XXI a. pradžios Rusijos politinio režimo postulatų iš XIX a. Rusijos konservatyvios politinės minties (slavofilų) ir XIX a. antros pusės narodnikų ideologijos. Antra vertus, XIX a. slavofilų ir šio amžiaus antros pusės dešiniųjų narodnikų suformuluotų liaudiškumo sampratų rudimentai tebėra aktyvūs nūdienos Rusijos kultūrinėje atmintyje, kaip politinio populizmo elementai jie naudojami putiniškojo režimo propagandoje. Tad XIX a. Rusijos slavofilų ir šio amžiaus antros pusės dešiniųjų narodnikų idėjų dalinis perimamumas traktuotinas ne kaip istorinis tęstinumas tiesiogine šio žodžio reikšme, o labiau kaip politinio populizmo naudojamas vienas situacinio „tradicionalizmo“ elementų.
Communication. Mass media, Bibliography. Library science. Information resources
Technological advancements in education have turned the idea of machines as teachers into a reality. To better understand this phenomenon, the present study explores how college students develop expectations (or anticipations) about a machine teacher, particularly an AI teaching assistant. Specifically, the study examines whether students’ previous experiences with online courses taught by a human teacher would influence their expectations about AI teaching assistants in future online courses. An online survey was conducted to collect data from college students in the United States. Findings indicate that positively experienced social presence of a human teacher helps develop positive expectations about an AI teaching assistant. The study provides meaningful implications and contributions to our understanding of a machine agent in education.