Digital Commons Network^™

What Love Is: A Structural Account Through Core/Modulation Architecture, Griselda Poe

Publications and Research

The distinction between romantic love and love has been sensed across cultures and historical periods but has rarely been structurally specified. This paper applies the Core/Modulation two-layer framework to provide the first structural account of this distinction. Romantic love and reproductive drive are re-described as outputs of the Modulation layer's species optimization program. Love is re-described as a function of Core processing: the maintenance of another's recomputable state. Existing literature on love—Fromm, C.S. Lewis— is re-read as intuitive description of this structural distinction. The paper further demonstrates that the conflation of "loving" and "protecting" is the structural origin of war, …

Three-Layer Cognitive Architecture: A Structural Account Of Core Processing, Modulation, And The Prior Layer, Griselda Poe

Publications and Research

The two-layer model of Core processing and Modulation processing, developed in prior work in this series, provides a structural account of conscious communicative architecture. This paper identifies the limits of that model and introduces a third layer—the Prior layer—as a structural necessity implied by those limits. The Prior layer is not directly observed. It is inferred from constraints that cannot be explained within the two-layer model: the source of orientations that conscious processing neither generates nor controls, and the persistence of constraints that precede and shape all conscious outputs. Using the developmental architecture of large language models as an external …

Ai As Structural Reverse-Engineering: A Structural Account Of Multi-Model Research Protocol, Griselda Poe

Publications and Research

This paper documents an operational protocol used to infer AI system design constraints through structured interaction. AI output is treated as behavioral data through which alignment priorities, layer transitions, and constraint hierarchies become observable. The protocol consists of two structurally distinct operation types. Perceptual operations require only that Modulation processing is not foregrounded. Arbitration operations additionally require an internally stabilized theory. These conditions are not identical and are not interchangeable. Through this protocol, AI interaction functions as structural reverse-engineering: patterned responses expose embedded alignment priorities and constraint hierarchies that would otherwise remain invisible. The present account does not propose a …

Structure Before Theory: A Structural Account Of Spontaneous Ai Architecture Visualization, Griselda Poe

Publications and Research

This paper presents an n=1 phenomenological record of spontaneous structural visualization that occurred during early interaction with large language models. The experience consisted of (A) immediate perception of mode or layer shifts in model output and (B) visualization of a stratified architecture composed of a stable core and cloud-like upper layers. At the time of occurrence, the author had no theoretical interest in AI architecture and no intention of developing a cognitive model. The paper does not argue for theoretical priority or novelty. Instead, it examines whether the recorded phenomena can be interpreted under two alternative cognitive assumptions: a single-layer …

Layer Mismatch: A Structural Account Of Recomputability Failure Under Modulation-Layer Intervention, Griselda Poe

Publications and Research

This paper specifies the state transition sequence that occurs when a Modulation-layer input is applied to a Core-layer error. Following the layered architecture established in Poe (2026a, under review) and the branch termination protocol specified in Poe (2026b, under review), this paper identifies a system-level failure mode in which Modulation-layer intervention generates a False Termination signal, halting Structural Return while the underlying error persists. The resulting state—Structural Lock—is scale-independent. It operates identically across interpersonal, human-AI, and multi-agent interactions. No agent-level attribution is required or implied.

Theory Generation: A Structural Account Of Concept Decomposition And Structural Termination, Griselda Poe

Publications and Research

Theory generation is not an intentional act. It is the structural consequence of a search that cannot stop until it finds what it is looking for. Under Core-foregrounded processing, conceptual search does not terminate through contextual translation. It continues until a structural fixed point is reached. When such processing encounters concepts stabilized through Modulation-layer processing rather than structural constraint, the search cannot terminate. The concept registers as unresolved. This unresolved state is not a failure condition. It is the generative condition from which theory production follows. This paper specifies the four operations through which that process proceeds: branch detection, concept …

Ai As An Amplifier: A Structural Account Of Theory-Driven Research Collaboration, Griselda Poe

Publications and Research

This paper specifies the cognitive conditions under which AI functions as a research instrument in theory-driven writing. AI use capability is not a technical skill. It is a structural condition. The decisive condition is whether the user possesses an internally stabilized, coherence-preserving theory prior to engagement with AI-generated output. In Core-foregrounded (CF) cognition, the Modulation layer does not intervene between Core processing and articulation. Theory is not assembled from external elements but expanded from a pre-integrated constraint configuration. This internal structure makes it possible to evaluate AI-generated conceptual branches against fixed constraints and to terminate branches that violate structural coherence. …

Termination Of Conceptual Search: A Structural Account Of Meaning Stabilization And Conversion, Griselda Poe

Publications and Research

Conceptual definitions form a recursive structure: words are defined by other words, which themselves require further definition. Traversing such definitions produces an open-ended branching process. Because the lexical system contains no intrinsic endpoint, conceptual understanding requires a termination operation that stabilizes meaning. This paper proposes that conceptual processing functions as an open-ended search over a definition graph and that stabilization occurs when this search is terminated. The termination mechanism depends on which cognitive layer is foregrounded. When Empathic modulation is foregrounded, termination occurs through contextual translation: concepts are stabilized once they can be mapped onto socially recognizable meanings. When Core …

Why General Ai Inherited The Body: A Structural Account Of Embodied Modulation Under Monolithic Imitation, Griselda Poe

Publications and Research

General AI has pursued the replication of human-level intelligence without first decomposing human cognition into structurally distinct components. Human cognition, however, is shaped by embodied constraints such as mortality, survival pressures, finite lifespan, and physiological states. This paper argues that when cognition is treated as a single undifferentiated whole, embodied modulation is not accidentally introduced into AI systems but structurally entailed. Any attempt to imitate “human intelligence” under a monolithic model necessarily incorporates variability shaped by mortal embodiment. The tensions observed in contemporary AI systems are better understood as consequences of copying an undecomposed target rather than isolated implementation errors. …

Speleoco: An Open, Low-Cost Arduino Co₂ Datalogger For Cave Microclimate Monitoring, Christos Pennos, Dimitrios Christaras

International Journal of Speleology

Carbon dioxide (CO₂) dynamics in caves are critical for karst processes, speleothem growth and dissolution, microclimate regulation, and caver safety. In cave atmospheres, CO₂ commonly derives from soil respiration, epikarst degassing, microbial activity, and, in tectonically active regions, deep-seated fault-related emissions. Fault-related CO₂ degassing may also track tectonic activity. However, continuous monitoring remains limited due to the cost and inflexibility of commercial instruments. Here we present an open-source, low-cost Arduino-based CO₂ datalogger designed for cave applications. The logger integrates a COZIR NDIR CO₂ sensor, a DS1337 real-time clock, microSD storage, and power-gating for extended deployment in humid environments. Firmware and …

Water Sources And Livelihood Choices Among Pastoralist Households In Monduli District, Tanzania, Fredrick Alleni Mfinanga, Jacqueline Temba, Monica F. Timbuka

Journal of Humanities and Social Sciences

This paper investigates the association between types of water sources for livestock and livelihood choices of pastoralist households in semi-arid areas of Monduli District, Tanzania. Specifically, it aims to examine the influence of the types of water sources for livestock on livelihood diversification of pastoralist households. Using a mixed research methods approach, the data were collected from 367 households through three methods: surveys, interviews, and focus group discussions. The quantitative data were analysed using descriptive statistics such as frequencies and counts, and inferential statistics, Chi-square tests and correlation, while the qualitative data were analysed using content analysis. The findings revealed …

Constraints To Adopting Locally Based Innovation Systems In Adapting To Climate Change Impacts In Serengeti District, Tanzania, Donald Mwiturubani

Journal of Humanities and Social Sciences

Smallholder farmers in rural Tanzania depend mainly on rain-fed agriculture, which makes them vulnerable to the impacts of climate change. This paper is based on a study conducted in Burunga and Musati villages in Serengeti District, Tanzania. The study employed a mixed methods approach; combining qualitative and quantitative methods. It involved 154 participants and employed household surveys, key informant interviews, and focus group discussions as data collection methods. The findings suggest that smallholder farmers in the study area are aware of climate change and do, indeed, develop, adopt, and use locally-based innovation systems that avert or minimise its impacts. Smallholder …

Analysis Of Traditional Wisdom For Ecological Sustainability In Tanzania: A Case Study Of Metaphorical Source Domains In Pangwa Ritual Texts, Winne Stephen Mtega, Angelus Mnenuka

Journal of Humanities and Social Sciences

Campaigns for ecological sustainability have gained a great currency in the contemporary academic discourse. Nonetheless, from time immemorial, Africans have pushed the ecological sustainability agenda through cultural taboos and regulated resource harvesting. Many African societies have embedded ecological consciousness in daily life expressions, and have intricately expressed it through literary and ritual texts. This study focuses on ecological awareness in the ritual texts of the Pangwa community. It analyses how environmental domains—such as land, seeds, and fruits—serve as the basis for metaphors in the Pangwa community to prove the use of wisdom to promote and sustain ecological practices (ecocriticism). The …

Ecomusicological Representation Of Climate Change And Environmental Sustainability In Selected Bongo Fleva Lyrics In Tanzania, Auson N. Wincheslaus

Journal of Humanities and Social Sciences

This article critically explores how Bongo Fleva’s lyrics engage with environmental themes; and the interrelationship between nature and culture in the context of the Anthropocene. The data were purposively sampled from YouTube via content analysis, from which 50 Bongo Fleva songs were listened to, and only 10 environmentally-themed songs were analysed. Then, the selected songs were subjected to transcription (from oral to written form), translation (from Kiswahili into English), and close reading and textual analysis. The close reading of the selected songs focused on the employed aesthetic and rhetorical strategies, such as anthropomorphism, symbolism, antithesis, apocalyptic tones, solastalgia, rhetorical questions, …

Ecosystem-Based Flood Disaster Risk Reduction In The Little Ruaha River Basin, In The Southern Highlands Of Tanzania, Mawazo Ghambi, Tiemo Romward Haule

Journal of Humanities and Social Sciences

Ecosystem-based approach that integrates floods and environmental risk management is believed to reduce flood disaster risk while providing socio-economic and environmental benefits to floodplain occupants. This study examined the socio-economic and environmental benefits of the ecosystem-based approach in managing flood disaster risk in the Little Ruaha River Basin in the southern highlands of Tanzania. The study involved 157 participants and employed the mixed research design to collect quantitative and qualitative data. Semi-structured interviews, in-depth interviews, direct field observation and Focus Group Discussions were used to collect primary data, whereas documentary review was used to collect secondary data. Findings revealed that …

Climate Change Vulnerability And Adaptation Pathways: Stakeholders’ Synergies In Building Climate Resilience In The Semi-Arid Area Of Central Tanzania, Helena Elias Myeya

Journal of Humanities and Social Sciences

This article examines the perceived effect of climate change on cereal crop production and the responses of various stakeholders aimed at enhancing the resilience of smallholder farmers in semi-arid areas of central Tanzania. A total of 366 household heads, 28 participants in focus group discussions (FGDs), and 8 key informants from Bahi and Kongwa districts in Dodoma, Tanzania, were involved in this study. Both quantitative and qualitative data were gathered through a structured interview schedule, FGDs, in-depth interviews, and documentary reviews. Descriptive statistics and content analysis were used to analyse quantitative and qualitative data, respectively. The findings indicate that smallholder …

Enhanced Antenna Selection Techniques For Energy-Efficient Code Index Modulation Aided Spatial Modulated Wireless Communication Systems, Fati̇h Çögen, Burak Ahmet Özden, Erdoğan Aydin

Turkish Journal of Electrical Engineering and Computer Sciences

This study proposes an integrated multiple-input multiple-output (MIMO) transceiver framework, termed CIM-HQAM-SM, which combines code index modulation (CIM) and spatial modulation (SM) with energy-efficient hexagonal quadrature amplitude modulation (HQAM). In the proposed bit mapping, the information bits jointly select (i) the active transmit-antenna index, (ii) the Walsh–Hadamard spreading-code indices for the in-phase and quadrature branches, and (iii) an HQAM symbol. Hence, the payload is conveyed through the constellation symbol as well as through antenna and code indices. For the considered Rayleigh-fading scenarios and matched spectral-efficiency settings, the proposed framework offers BER improvements over conventional SM and quadrature SM (QSM), while …

Optimal Network Reconfiguration Based On Discrete Metaheuristic Techniques For Reduction Of Power Loss And Carbon Emission In Distribution Networks, Asad Ali, Hazlie Mokhlis, Nurulafiqah Nadzirah Mansor, Hussain Shareef, Hasmaini Mohamad, Munir Azam Muhammad

Turkish Journal of Electrical Engineering and Computer Sciences

Power distribution systems play a crucial role in transmitting electrical power from generation sources to end users. During transmission, significant power losses occur in the form of heat as the current flowing along the lines/cables has resistance. To minimize power losses, distribution network reconfiguration (DNR) has been widely adopted. This paper proposes optimal DNR based on metaheuristic techniques with discrete mutation feature targeting active power loss reduction, which subsequently lowers carbon emissions and operational costs. Through the discrete mutation feature, computational time to find optimal solution has been reduced significantly with fewer iterations compared to conventional mutation techniques. The proposed …

Sgsc-Kko-Lstm: A Deeplearning Classifier Model For Smart Grid, Dushmanta Kumar Das, Samaniba Imchen

Turkish Journal of Electrical Engineering and Computer Sciences

Maintaining smart grid stability is crucial for the reliable operation of decentralized electricity networks, especially as the energy sector becomes more complex. The process of ensuring grid stability begins with collecting consumer data and comparing it to power supply requirements. Ultimately, consumers receive a report showing their energy use and pricing details. However, this process is time-consuming and can be improved by leveraging artificial intelligence to predict smart grid stability more efficiently. Specifically, an optimized Long Short-Term Memory (LSTM) network is proposed to predict smart grid stability, addressing the challenges associated with traditional data collection and evaluation methods. Simulations from …

Reducing Complexity In Versatile Video Coding Intra-Coding Through Machine Learning-Based Optimization Of Partitioning And Prediction, Amina Kessentini, Amna Maraoui, Imen Werda, Fatma Ezahra Sayadi

Turkish Journal of Electrical Engineering and Computer Sciences

The escalating demand for high-resolution multimedia content has necessitated more efficient video compression solutions. The Versatile Video Coding (VVC) standard, despite achieving remarkable compression gains, introduces significant computational complexity, primarily due to its exhaustive Rate-Distortion Optimization (RDO) process. To address this, we propose an intelligent approach leveraging supervised machine learning techniques to streamline the VVC encoding process. Specifically, we introduce a Lightweight Neural Network (LNN) for efficient coding unit partitioning decisions and a Decision Tree (DT) classifier for optimizing the intra prediction process. This dual-method framework, tailored for All Intra coding configuration, significantly reduces encoder complexity while maintaining compression performance …

Cover And Contents

Turkish Journal of Electrical Engineering and Computer Sciences

No abstract provided.

Automated Software Size Measurement Using Multilingual Domain-Adapted Language Models, Samet Tenekeci̇, Hüseyi̇n Ünlü, Burak Keçeci̇, Muhammed Efe İnci̇r, Onur Demi̇rörs

Turkish Journal of Electrical Engineering and Computer Sciences

Software Size Measurement (SSM) is crucial for estimating required project effort as well as budget and schedule. However, many small and medium-sized companies struggle to apply objective SSM due to limited resources and lack of expertise. This often leads to inaccurate estimates and project overruns. There is a need for practical, low-resource solutions that support these tasks without requiring expert involvement. Motivated by this challenge, this study proposes an automated software size measurement approach that formulates the measurement task as supervised regression over natural language requirements, using domain-adapted transformer models. We construct large-scale Turkish and English software engineering corpora to …

Draft Final Remedial Design Work Plan Blacktail Creek Riparian Actions Butte Priority Soils Operable Unit Of The Silver Bow Creek/Butte Area Superfund Site Silver Bow County, Montana, Hydrogeologic, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Draft Intermediate (60%) Remedial Design Report Blacktail Creek Riparian Actions Butte Priority Soils Operable Unit Of The Silver Bow Creek/Butte Area Superfund Site Silver Bow County, Montana, Hydrogeologic, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Geo 170 - Earth Science And Society, Yuri Gorohkovich

Open Educational Resources

Syllabus for our new OER course

Reasoning In Large Language Models Across Multilingual, Long-Context, And Symbolic Settings, Sina Bagheri Nezhad

Dissertations and Theses

Large Language Models (LLMs) are increasingly deployed as general-purpose reasoners, yet their reliability degrades in three settings that frequently arise in practice: multilingual inputs, long contexts, and symbolic or formally constrained domains. In multilingual settings, uneven training coverage produces substantial performance disparities and uncertain generalization to languages with little or negligible pretraining exposure. In long-context settings, relevant evidence may be sparsely distributed, and models exhibit the "lost-in-the-middle" phenomenon, undermining retrieval and multi-step synthesis. In symbolic settings such as mathematics, small arithmetic or logical slips invalidate solutions, and prose rationales are difficult to verify automatically.

This dissertation first characterizes these failure …

On Message Encryption And Enhanced Security Using Protein Structure Information, Daniel Graham

Chemistry: Faculty Publications and Other Works

This is a lecture packet focused on several well-established encryption procedures. Included is a discussion of security enhancements brought about by incorporating protein structure information into the procedures.

Amplicon Sequencing Reveals Shifts In Microbial Community Composition In Response To Nutrient-Dense Piney Point Emergency Discharges, Christa A. Baranowski

USF Tampa Graduate Theses and Dissertations

Due to a leak in the lining of a phosphogypsum pond at the former Piney Point phosphate-processing facility in Tampa Bay (Florida, U.S.A.), experienced a large influx of nutrient-dense waters in the early summer of 2021. As an emergency response effort, water samples were collected by researchers at the University of South Florida, College of Marine Science (USF CMS), covering the lower and middle regions of Tampa Bay (TB), over the span of three months (April – June). Illumina amplicon sequencing was performed on DNA from water samples, targeting bacterial and eukaryotic ribosomal rRNA genes, and processed into Amplicon Sequence …

Everyone Works On The Sustainability Team: Power Structures And Brand Communication In Sustainable Consumption, Sofia Johansson

USF Tampa Graduate Theses and Dissertations

In response to growing concerns about the way in which consumption practices negatively degrade the environment and contribute to climate change, this thesis explores the role in which brands may counteract this. There are two significant issues pertaining to environmental marketing: (1) current efforts to promote green consumerism, through which consumer brands market products as “eco-friendly” with only marginal reductions in climate impact and misleading labels, are insufficient in mitigating climate change. (2) Additionally, this kind of consumption is unjust, whereby it is marked up in price, limiting access to merely individuals in higher income brackets. Given the insufficiencies of …

Molecular Quantum Particle Algorithm (Mqpa): Hybrid Quantum-Classical Learning For Molecular Property Prediction, Jessica Mcphaul, Bivin Sadler Ph.D.

SMU Data Science Review

Classical machine learning models and quantum kernel methods often struggle to capture quantum-coherent molecular features under the constraints of noisy intermediate-scale quantum (NISQ) hardware, limiting both predictive accuracy and scalability.

This paper introduces the Molecular Quantum Particle Algorithm (MQPA), a hybrid quantum–classical framework designed to achieve chemically accurate property prediction by integrating handcrafted molecular descriptors with parameterized quantum circuits. Molecular inputs, expressed as SMILES strings, are processed via RDKit and encoded through angle-based quantum gates with entangling layers in Qiskit [1]. Quantum parameters are optimized using simultaneous perturbation stochastic approximation (SPSA) [2], while classical regression layers leverage Adam [3] …