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This collection brings together the Knight Alzheimer Disease Research Center (ADRC) Data Freeze datasets published through Digital Commons Data@Becker. Each Data Freeze represents a distinct snapshot of the ADRC research data available at a specific point in time. Individual Data Freeze datasets are assigned separate DOIs to preserve versioned releases, while this collection provides a single entry point for browsing the complete series.

LC-MS/MS raw data and integrated peak areas for annotated lipid species for the manuscript "Beyond the surface: plasmalogens are dispensable for retinal integrity and fertility in the mouse".

RESUMEN Este artículo examina la ecología de la información como una infraestructura política que determina qué mensajes alcanzan visibilidad, qué fuentes conservan credibilidad y qué interpretaciones orientan la decisión pública. El estudio adopta una revisión documental y una síntesis conceptual de obras sobre propaganda, teoría de la comunicación, economía de la atención, desorden informativo, polarización y gobernanza de plataformas. Los hallazgos señalan una continuidad entre la propaganda de masas y las formas digitales de influencia, aunque la arquitectura de intermediación cambió por la multiplicación de emisores, la recomendación automática y la circulación entre medios, redes sociales y canales cerrados. La falsedad constituye solo una parte del problema. También intervienen la selección de agenda, el encuadre, la filtración interesada de información auténtica, la repetición, la coordinación distribuida y los incentivos comerciales que premian reacción inmediata. La erosión de confianza debilita la corrección factual y eleva los costos de cooperación institucional. El artículo sostiene que una respuesta democrática requiere periodismo independiente, transparencia pública, educación mediática, acceso a datos para investigación y reglas de plataforma compatibles con libertad de expresión y debido proceso. ABSTRACT This paper examines information ecology as a political infrastructure that determines which messages gain visibility, which sources retain credibility, and which interpretations guide public decisions. The study uses documentary review and conceptual synthesis across scholarship on propaganda, communication theory, the attention economy, information disorder, polarization, and platform governance. The findings identify continuity between mass propaganda and digital influence, although intermediary structures changed through a wider range of speakers, automated recommendation, and circulation across news media, social networks, and closed channels. Falsehood is only one part of the problem. Agenda selection, framing, selective disclosure of authentic information, repetition, distributed coordination, and commercial incentives that reward immediate reaction also shape the public sphere. Declining trust weakens factual correction and raises the institutional cost of cooperation. The article argues that democratic protection requires independent journalism, public transparency, media education, research access to platform data, and platform rules consistent with freedom of expression and due process.

Instructions, code, and data for Debt and Assets.

RESUMEN. Este artículo analiza la manipulación algorítmica como una arquitectura de influencia que articula producción de contenidos, redes coordinadas de distribución y sistemas automatizados de priorización. El estudio adopta una revisión documental de carácter analítico y examina propaganda computacional, cuentas automatizadas, simulación de apoyo social, microsegmentación, circulación transversal entre plataformas y explotación de señales de popularidad. También estudia la expansión de medios sintéticos, la suplantación audiovisual y la pérdida de confianza en registros auténticos. Los hallazgos indican que el poder de estas prácticas no depende de un algoritmo aislado, sino de la convergencia entre objetivos políticos, infraestructura organizacional, opacidad de identidad y reglas de visibilidad. La detección técnica aporta señales útiles, aunque no prueba por sí sola la autoría ni la intención. La verificación de procedencia, la corroboración externa, los protocolos institucionales y la transparencia regulatoria forman una defensa de varias capas. El artículo concluye que la protección de la deliberación pública exige controles proporcionales, acceso responsable a datos, alfabetización mediática y garantías para la libertad de expresión. ABSTRACT. This paper analyzes algorithmic manipulation as an influence architecture that connects content production, coordinated distribution networks, and automated prioritization systems. The study uses an analytical documentary review and examines computational propaganda, automated accounts, simulated social support, microtargeting, cross-platform circulation, and the exploitation of popularity signals. It also studies synthetic media, audiovisual impersonation, and the decline of trust in authentic records. The findings show that the power of these practices does not depend on one isolated algorithm. It arises from political objectives, organizational infrastructure, identity opacity, and visibility rules. Technical detection supplies useful indicators, but it does not establish authorship or intent by itself. Provenance verification, external corroboration, institutional protocols, and regulatory transparency form a layered defense. The article concludes that the protection of public deliberation requires proportional controls, responsible access to data, media literacy, and safeguards for freedom of expression.

AntEngage Empathy Conversation Dataset (Version 1.0.0) is an open-access dataset containing 4,008 AI-synthesized multi-turn empathy-focused conversations designed for research and development in natural language processing, conversational AI, and affective computing. The dataset was created by AntEngage Technology Private Limited as part of the AntEngage Language Model (AELM) initiative. Each conversation represents realistic emotional support interactions involving situations such as caregiver burnout, grief, loneliness, workplace stress, parenting challenges, and emotional exhaustion. Dialogues were generated using a structured synthetic data generation pipeline followed by automated quality verification to improve diversity, coherence, naturalness, and safety. No conversations were collected from real individuals. The dataset contains no personally identifiable information (PII) and consists entirely of AI-generated content intended for research and model development. The primary objective of this dataset is to support the development and evaluation of empathetic dialogue systems, conversational agents, instruction tuning datasets, and language models capable of producing supportive and emotionally appropriate responses. Dataset Characteristics • 4,008 conversations • 79,616 dialogue turns • English language • Multi-turn dialogue format • JSONL and CSV formats • License: Creative Commons Attribution 4.0 International (CC BY 4.0) Potential Applications • Empathetic dialogue generation • Conversational AI research • Instruction tuning for large language models • Affective computing • Mental health NLP research • Dialogue system benchmarking • Human-AI interaction research This dataset is intended solely for research and educational purposes. Although the conversations model supportive communication, they are not a substitute for professional medical or mental health advice.

RESUMEN. Este artículo examina la desinformación digital como instrumento de influencia política y coerción indirecta. El estudio adopta una revisión documental de carácter analítico y distingue entre información falsa sin intención de daño, información falsa difundida con intención lesiva e información verdadera usada de forma perjudicial. El análisis identifica técnicas de engaño dentro de los mensajes, patrones de campaña basados en volumen, repetición y coordinación, y mecanismos de difusión que aprovechan la economía de la atención, los vacíos informativos y la confianza entre comunidades. Los hallazgos señalan que el daño no depende solo de la falsedad, sino también de la arquitectura de circulación, la identidad política y la erosión de la confianza institucional. La discusión sostiene que la respuesta pública debe integrar alfabetización mediática, comunicación institucional oportuna, verificación, inoculación preventiva, transparencia de plataformas y criterios probatorios para la atribución, sin recurrir a censura general ni a vigilancia indiscriminada. ABSTRACT. The paper examines digital disinformation as an instrument of political influence and indirect coercion. The study uses an analytical documentary review and separates false information without harmful intent, false information spread with harmful intent, and true information used for harmful purposes. The analysis identifies deception techniques within messages, campaign patterns based on volume, repetition, and coordination, and circulation mechanisms that exploit attention markets, information voids, and trust inside communities. The findings indicate that harm depends not only on falsehood but also on circulation architecture, political identity, and the erosion of institutional trust. The discussion argues that public responses should combine media literacy, timely institutional communication, fact verification, preventive inoculation, platform transparency, and evidentiary standards for attribution, without general censorship or indiscriminate surveillance.

In pharmaceutical manufacturing, terminal high-efficiency particulate air (HEPA) filters are a critical barrier against airborne microbiota, yet maintenance is often performed on fixed schedules. This case study evaluates statistical process control (SPC) rules for low-count airborne Colony Forming Unit (CFU) data from Class C cleanrooms and assesses whether they can support HEPA filter maintenance decisions beyond a time-based program. Using 813 quarterly monitoring records collected over three and a half years from 79 HEPA filters, a distribution-based alert rule was developed by fitting a negative binomial model to discrete, overdispersed counts, combining discrete outlier diagnostics, a 95th-percentile control limit, and the Class C specification limit. The attached documents include the CFU data set, a Demo file data set, the Discrete SPC app and spc_core codes in R. Also a Readme file with the instructions on how to use the R code is included.

Sorption experiment and modelling results

These two Excel files contain qualitative datasets generated by large language models using single-run prompts to simulate a hypothetical alternative history of the Soviet Union without Joseph Stalin as leader. In this process, alternative political, economic, and institutional pathways have been conceptualized counterfactually to support a thought experiment. The current paper is under review, so anyone using the dataset should handle it carefully and cite it appropriately.