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This paper introduces the Morphological Participation Index (MPI), a substrate-agnostic framework for estimating whether a system’s morphology can plausibly support strongly integrated, coherence-sensitive, trace-rich, and temporally scaffolded dynamics. “Participation” refers to the degree to which morphology actively contributes to, constrains, and scaffolds the integrated, trace-bearing, and temporally organized dynamics available to a system. The immediate motivation comes from two adjoining lines of work: spectral approaches to resistance to decomposition, and recent proposals by Schneider and Bailey concerning prototime, […]

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Large language models (LLMs) represent a cutting-edge breakthrough in the deep learning models designed for processing human languages. This study created a local LLM that used Book Four of the Civil Code of Catalonia relating to Successions and the regulations of the Notary Profession of Spain for summarization and answering questions in a context of increased security. The model summarized and replied to specific questions in a reasonable manner but was not absent of information loss and contextual […]

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Numerical preprocessing remains an important component of tabular deep learning, where the representation of continuous features can strongly affect downstream performance. Although its importance is well established for classical statistical and machine learning models, the role of explicit numerical preprocessing in tabular deep learning remains less well understood. In this work, we study this question with a focus on spline-based numerical encodings. We investigate three spline families for encoding numerical features, namely B-splines, M-splines, and integrated splines (I-splines), […]

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Ultrasonic cyberattacks represent an emerging threat vector capable of exfiltrating information even from high-security systems. Modern computing devices equipped with integrated speakers and microphones can generate ultrasonic emissions that may be exploited for covert communication. Previous studies have demonstrated that malicious software can utilize ultrasonic audio channels to establish communication links between otherwise isolated systems, enabling data leakage from air-gapped environments by relaying information through acoustic signals. Experimental results have shown that data can be transmitted at rates […]

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As companies grow, they can expand their offerings, reach new customers and markets, enhance profitability, and position themselves ahead of competitors. Whether trying to expand their company size by adding new departments or increase revenue by improving productivity per employee, companies can achieve growth through various strategies. One of the strongest company growth strategies is retaining skilled employees who drive productivity, innovation, morale, and customer satisfaction. Employee retention is a company’s ability to maintain a stable workforce by […]

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The Quantum Darwinist Theory of Consciousness (QDT) and the Prototime Interpretation (PT) characterize localized conscious basins in terms of spectral integration, PT-participation, recursive coherence, witness redundancy, and temporally ordered record formation [7–9]. An upstream question has remained largely implicit in that program: what sort of morphology makes such dynamics structurally plausible? This paper argues that morphology constitutes the architectural precondition of basin formation, and that the Morphological Participation Index (MPI; Montes 5) can make that precondition operational. Architecture, […]

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The rapid deployment of large language model (LLM) based agents in production environments has surfaced a critical engineering problem: as agent tasks grow longer and more complex, task execution reliability increasingly depends not on the underlying model’s capabilities, but on the infrastructure layer that wraps around it—the agent execution harness. This dependence suggests that the harness, not the model, is the binding constraint for real-world agent system performance. We treat the harness as a unified research object deserving […]

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Community reintegration of formerly incarcerated individuals is one of the most pressing challenges confronting criminal justice systems worldwide. High recidivism rates, fragmented service delivery, stigma, and inadequate coordination among correctional agencies, social service providers, and communities collectively undermine successful reintegration outcomes. Artificial intelligence (AI) offers transformative potential to address these systemic deficiencies through data-driven risk assessment, personalised service matching, and continuous behavioural monitoring. However, no comprehensive, ethically grounded architectural framework currently exists that integrates these capabilities into a […]

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We present GaroNMT, a neural machine translation system for Garo (ISO 639-3: grt), a Tibeto-Burman language spoken by approximately one million speakers in Northeast India, written in a Latin-based orthography with distinctive glottal stop and nasal characters. Despite its significant speaker population, Garo has received virtually no attention in NLP research, with no publicly available machine translation system prior to this work. We fine-tune NLLB-200-distilled-600M by introducing a custom language token (grt_Latn), and conduct a systematic ablation study […]

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