Digital Commons Network^™

Challenges And Best Practices Of Regional Innovation Ecosystems, Mahnaz Asgari Sooran

Miners Solving for Tomorrow Research Conference

Many places around the world are developing regional innovation ecosystems to spur regional economic. Many innovation ecosystems fail or barely maintain their initial momentum after a few years. In this paper, we identified challenges and best practices facing innovation ecosystems interviews with the innovation ecosystem stakeholders. We employed the MIT REAP (Regional Entrepreneurship Acceleration Program) model to categorize the five main stakeholders of the innovation ecosystem: entrepreneurs, universities, industry, risk capital, and government. Our initial results indicated the following: (a) Access to capital and talented workforce; (b) Stakeholder discovery process is one of the critical areas to understand the basic …

Simulating Thermal Diffusion Through Image-Derived Microstructures Of Ceramic Matrix Composites, Matik Heskin

Miners Solving for Tomorrow Research Conference

Thermal energy transport in materials can be effectively modeled using finite element software such as COMSOL. Experimentally measured or NIST–JANAF thermal conductivity data can be used to represent material behavior within these simulations. For heterogeneous or composite materials, effective properties are often approximated using rule-of-mixtures calculations. However, this overlooks the nuanced effects caused by complex microstructural geometry. To address this limitation, imaging and coding tools such as MATLAB can be used to process scanning electron microscopy (SEM) images. By thresholding the images to distinguish constituent materials, a representative mesh can be generated and imported into an FEM program. This approach …

Distributed Control Plane For Cross-Silo Federated Learning, Rabin Pandey

Miners Solving for Tomorrow Research Conference

Cross-silo federated learning (FL) trains shared models across geographically distributed institutions without centralizing raw data, but its reliance on wide-area networks makes round completion time highly sensitive to heterogeneous link conditions, congestion, and straggler clients. Existing SDN-based FL frameworks address this through centralized traffic engineering, an approach that breaks down when silos span independent administrative domains where no single entity can maintain complete, timely network knowledge. We replace the centralized control plane with a fully distributed overlay in which each silo gateway operates as an equal peer, continuously probing local links, exchanging EWMA-smoothed metrics via bounded gossip, and computing least-cost …

Transition Metal Chalcogenide As Multifunctional Biosenser To Detect Neurochemicals, Amitav Sen

Miners Solving for Tomorrow Research Conference

The development of highly sensitive real-time sensing platforms for selectively detecting dopamine (DA) and norepinephrine (NE) is of significant clinical importance since these are closely associated with several neurodegenerative disorders. Herein, we report copper telluride (Cu₂Te) nanostructure as a bifunctional electrocatalyst for the simultaneous detection of dopamine and norepinephrine. Cu₂Te exhibits excellent electrocatalytic activity toward both DA and NE oxidation, as demonstrated by detailed electrochemical measurements. High sensitivities of 24 and 40 µA cm⁻² µM⁻¹ for DA and NE, respectively, were obtained with a wide linear detection range of 10–200 nM and low limit of detection (LOD), 31 nM for …

Human Intention Prediction Using Cnn And Lstm Networks In Physical Human–Robot Interactions, Khosro Ghorbani Zadeh

Miners Solving for Tomorrow Research Conference

Advances in robotics and artificial intelligence have increased expectations for interactive robots in eldercare and assistive applications. A key challenge in creating safe and effective systems is accurately recognizing human intent and translating it into meaningful commands for robots to follow. Traditional physics-based models often fail to fully represent human force interactions due to their dynamic nature, while neural networks provide a promising alternative for predicting force-movement intentions. Multi-layer perceptrons (MLPs) show potential, however, they struggle with temporal dependencies and generalization. Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNNs) help address these limitations. This study compares these architectures …

Toward Sustainable 3d Printable Cementitious Materials: Low-Carbon Design With Fiber Reinforcement, Nima Mahmoudzadeh Vaziri

Miners Solving for Tomorrow Research Conference

3D printing of cementitious materials, as an emerging construction technology, faces challenges in both mechanical performance and sustainability. Conventional mixture designs rely on high cement contents, leading to increased CO2 emissions, while printed elements often exhibit brittle behavior with limited crack resistance and reduced post-cracking performance. This study investigates the development of low-carbon 3D printed cementitious composites using environmentally friendly supplementary cementitious materials (SCMs) and fillers, combined with fiber reinforcement to enhance mechanical performance. Locally available SCMs and fillers were incorporated to significantly reduce cement content (>40%) and improve sustainability. Fiber reinforcement was introduced to mitigate brittleness and enhance …

Ai-Driven Frameworks For Mitigating Rockfall Hazards, Unstable Ground Condition And Improving Safety In Underground Mine Through Thermal Imaging, Akhrorbek Narmatov

Miners Solving for Tomorrow Research Conference

Scaling, the removal of loose rocks from excavation walls to prevent rockfalls is a critical safety procedure in underground mining operations. Approximately a quarter of fatal mining accidents are due to rockfalls. Detecting unstable rocks during scaling and assessing ground stability remain challenging due to limited visibility, dust, and environmental conditions.

Excavation disturbs the in-situ stress state, causing stress redistribution, fracture propagation, and the formation of discontinuities that lead to loose rock blocks. Ventilation airflow affects heat transfer at exposed surfaces, amplifying temperature contrasts between intact rock and fractured blocks associated with instability.

Current practices rely on manual inspection, requiring …

Robust Federated Learning With Strategic Adversaries, Manoj Twarakavi

Miners Solving for Tomorrow Research Conference

Federated Learning (FL) leverages the intelligence of untrusted distributed devices through collaborative training. This makes the training process susceptible to malicious behavior. Existing defense mechanisms largely consider an adversary who attacks a proactive FL server without any adaptability. However, they overlook the presence of a strategic adversary. To address this challenge, our work proposes a Robust Game-theoretic framework where the adversary is both strategic and is equipped with the capability of performing large-scale poisoning attacks.

Leveraging Artificial Intelligence For Transformative Education: Challenges And Recommendations, Papia Bawa

Journal of Research Initiatives

The sheer force with which GPT models are inundating business, education and economic fields speaks to its ability to not only transform the ways in which we interact and act but also disrupt these ways. This systematic literature review applies the PSALSAR method to synthesize findings from 72 articles on AI applications in education, emphasizing its transformative potential across various domains. AI is transforming personalized learning by customizing content and feedback to individual needs, addressing challenges like data privacy and ethical concerns. It enhances administrative efficiency through automation and data-driven decision-making, improving institutional performance while managing biases and maintaining human …

Crowdsourcing Literary Recovery Using Iterative Search Techniques, Jean Lee Cole

Feminist Pedagogy

The Literary Recovery assignment teaches students how to develop keyword search search techniques to locate literary works and authors in online databases and text repositories. Using the assignment in a collaborative course project provides the benefit of crowdsourcing recovery efforts for prolific authors or groups of authors.

No Border Wall Press Releases, No Border Wall Coalition

Border Wall / Border Security Documents

No abstract provided.

Documents Compiled By The No Border Wall Coalition, No Border Wall Coaltion

Border Wall / Border Security Documents

No abstract provided.

Immigration Reform Could Bring More Walls To Texas, Scott Nichol

Border Wall / Border Security Documents

No abstract provided.

Judge Salinas Buys Into The Border Wall, Scott Nichol

Border Wall / Border Security Documents

No abstract provided.

Scenario-Based Pareto Analysis For Multi-Objective Optimization Of Process Parameters To Improve Life Cycle Impacts: Case Study Of Ge Production, Dennis Dadzie

Miners Solving for Tomorrow Research Conference

Growing demand for critical minerals increases the need for clear evidence on the environmental burdens of their production. Life‑cycle assessment (LCA) quantifies impacts, but it does not by itself show how to navigate competing environmental performance improvement goals. We examine 63 process configurations for single‑crystal germanium made via chlorinated distillation using five indicators: global warming potential (GWP), water consumption (WC), fine particulate matter (FPM), terrestrial acidification (TA), and cumulative energy demand (CED). Across scenarios, WC is negatively correlated with GWP, weakly related to FPM, TA, and CED, while the other four indicators are strongly positively correlated. Pareto analysis highlights a …

Virtual Fences And Border Walls: Billions Wasted On A False Sense Of Security, Scott Nichol

Border Wall / Border Security Documents

No abstract provided.

Assessing Radon And Radon Progeny Deposition On Simulated Lung Filter System: Effects Of Cigarette And E-Cigarette Use Based On The Icrp Model, Manuela Isabel Arenas Alvarez

Miners Solving for Tomorrow Research Conference

This project investigates the potential interaction between radon exposure and e-cigarette aerosols, focusing on how radon progeny deposit in the lungs under combined conditions. An experimental system was developed to simulate regional lung deposition based on the International Commission on Radiological Protection (ICRP) model. The setup uses a filter-based design and a custom modular atomizer to generate stable aerosols, with four commercial plastic filters evaluated. Initial results demonstrate reproducible filtration behavior and a total deposition pattern matching ICRP predictions within 21% error. Ongoing work aims to improve agreement with regional deposition curves and enable combined radon–aerosol exposure experiments. This platform …

Assessing The Effects Of Scale-Dependent Representation Of River Networks On Hydrologic Prediction, Hari Dhital

Miners Solving for Tomorrow Research Conference

Accurate hydrologic prediction at relevant spatial scales is essential for flood risk management. This study explores how spatial scale affects model parameters and simulation outcomes in the Hillslope Link Model (HLM). This was motivated by HLM implementation within the Next Generation Water Resources Modeling (NextGen) framework for the U.S. National Water Model. Since NextGen alters HLM's spatial scale from hillslopes to catchments, we assess how this change affects runoff generation and routing. We implement HLM at both scales using identical, predetermined parameters without calibration to isolate spatial discretization effects. Using approximately ten years of precipitation and streamflow data from watersheds …

Evaluation Of National Water Model Long-Range Streamflow Forecasts In Missouri, Sujan Maharjan

Miners Solving for Tomorrow Research Conference

Long-range river stage forecasts are increasingly used to support barge scheduling along the Missouri and Mississippi River navigation corridor. The reliability of these forecasts over extended lead times remains uncertain, particularly in regulated systems influenced by upstream dam operations. This study evaluates the lead-time-dependent performance of National Water Model long-range forecasts at eleven U.S. Geological Survey stations from Rulo to Thebes during 2019–2024. Results show that forecast skill does not decline smoothly with time but exhibits station-specific dips at lead times corresponding to hydraulic travel from major control structures. These periods coincide withstage bias and dispersion, indicating elevated operational uncertainty. …

Evaluation Of Channel Routing Module In The Nextgen National Water Model, Md Saiduzzaman

Miners Solving for Tomorrow Research Conference

The Next Generation Water Resources Modeling (NextGen) framework has a modular structure that enables the integration of multiple hydrologic models with channel routing processes. Within NextGen, the T-Route model performs channel routing using vector-based river networks and supports a hybrid routing approach within a single watershed. This study evaluates the hydraulic diffusive wave routing method implemented in T-Route and compares its performance with the operational Muskingum-Cunge routing used in the National Water Model. The primary objective is to assess the operational capability of streamflow data assimilation across different routing methods using an extensive network of streamflow observations. The routing models …

Controlled Gelation Of Co₂-Resistant Polymer Systems For Improved Conformance In Co₂-Eor, Maryam Sharifi Paroushi

Miners Solving for Tomorrow Research Conference

This presentation introduces a CO₂-resistant hydrogel developed to control fluid movement and improve CO₂ injection performance in subsurface reservoirs for Enhanced Oil Recovery (EOR) and Carbon Capture and Storage (CCS). Conventional polymer gels often lose strength in CO₂-rich environments, resulting in weak plugging, early breakdown, and ineffective flow control. To address this limitation, a sulfonated HPAM-based gel system crosslinked with chromium was developed. The effects of polymer concentration, molecular weight, crosslinker ratio, ionic strength, and pH were investigated to better understand gelation behavior and performance. The formulation exhibited controlled gelation, strong resistance to temperature and CO₂, and minimal shrinkage over …

Empirical Evaluation Of Policy-Based Reinforcement Learning For Dynamic Service Control In An M/M/1 Queue, Joseph Walton

Miners Solving for Tomorrow Research Conference

While reinforcement learning has been increasingly applied to stochastic control, limited work examines policy-based methods in queuing environments modeled as semi-Markov decision processes (SMDP). This study investigates how policy-based reinforcement learning (RL) algorithms perform when applied to service rate control in an M/M/1 queue, a common queuing model for manufacturing and service systems. The problem is formulated as an SMDP in which decisions occur at each new service, allowing an agent to select different service rates from a finite set of speeds, aiming to minimize an objective function that manages system congestion and energy costs. Three policy-based reinforcement learning algorithms, …

Structural Analysis On Iron Phosphate Glasses After Dechlorination Of Mixed Chloride Waste Forms, Lucas Greiner

Miners Solving for Tomorrow Research Conference

Molten salt reactors (MSRs) require durable waste forms for immobilizing halide-rich salts. This study examines iron phosphate glasses derived from a simple salt mixture (SSM), focusing on the effect of Fe₂O₃ additions (2.5–10 wt%) on structure and phase stability. Intermediates were processed at 300–600 °C and vitrified at 1050 °C. Raman spectroscopy and HPLC show that increasing iron content depolymerizes the phosphate network, shifting from Q² toward Q¹ species and reducing chain length. XRD confirms amorphous behavior for ≤7.5 wt% Fe₂O₃, while 10 wt% shows crystallization, with KFeP₂O₇ observed in samples processed at 400 °C. Despite reduced connectivity, iron enhances …

Preventive Maintenance Scheduling Using Artificial Intelligence And Decision Support Agent, Samiksha Aryal

Miners Solving for Tomorrow Research Conference

Preventive Maintenance models have traditionally relied on a time-based maintenance model, which uses fixed statistical distribution to represent the time-to-failure (TTF). The requirement of data-driven models and automated decision-making systems have become essential for modern manufacturing systems. The use of fixed statistical distribution limits the ability of existing models in producing solutions in real-time. Our model overcomes these limitations by implementing an empirical distribution to represent TTF. The empirical distribution is generated using a neural network which eliminates noise from the raw maintenance log. Renewal Reward Theorem (RRT) is implemented to efficiently provide maintenance threshold in real time. The use …

Robustness Of Fuzzy Artmap To Adversarial Attacks And Progressive Adversarial Training For Streaming Learning, Shane Cairns

Miners Solving for Tomorrow Research Conference

Incremental learners deployed on streaming data must remain robust to evolving adversarial perturbations, yet most adversarial-robustness studies assume offline multi-epoch training with repeated access to historical data. We investigate adversarial robustness in Fuzzy ARTMAP, a prototype-based Adaptive Resonance Theory model that supports single-pass learning without replay. We propose WB-Softmax, a differentiable relaxation that aggregates category-level activations into class-level scores for gradient-based attacks. WB-Softmax PGD achieves 89–100% attack success on vanilla models, exceeding transfer and query-based baselines. We then study adversarial training under true streaming constraints by comparing offline versus online adversarial example generation and standard versus selective updates. Offline adversarial …

No Border Wall Coalition Letters To Elected Officials, Scott Nichol, No Border Wall Coalition

Border Wall / Border Security Documents

No abstract provided.

Changes In 25(Oh)D Concentration, Bone Resorption Markers And Physical Performance Due To Sun Exposure, Diet And Training Load Among Professional Women Handball Players During The Half-Year Training Season, Sorin Dacian Buhas, Zbigniew Jastrzębski, Paul Florian Dragos, Marius Alin Marinau, Maria Skalska, Mirela Stef, Joanna Jastrzębska, Mihai Sandra, Dana Ioana Cristea

Baltic Journal of Health and Physical Activity

Background: The aim of the study was to demonstrate changes in 25(OH)D concentration, bone resorption indicators and physical fitness in female handball players as a result of their exposure to the sun, diet and exercise load during the six-month training period from mid-March to mid-September, i.e. the time when the sun exposure is the highest during the calendar year. Twenty-two women handball players participated in the study. Due to the random occurrences and exclusion criteria, 20 players completed the project. Biochemical analysis of blood, aerobic capacity, running speed and power tests (Wingate test, squat jump, counter movement jump, etc.) was …

There Is Turbulence In The Vuca World: A Path To Learning From The Micro- Environments Of Decision-Makers And Their Leadership Acumen, Bernard L. Simonin, Paul Lambert

Arab Economic and Business Journal

Decision-makers and researchers continue to ponder on how to cope with today’s volatile, uncertain, complex, and ambiguous environments (VUCA). The catch-all expression “it is a VUCA world” has gained popularity while raising some concerns on its applicability. To date, much of the focus has been in association with large-scale events of a negative nature; research has remained mostly conceptual with almost no extensive empirical investigation centered on the fully unpacked VUCA construct. This study examines the interplay between VUCA elements, turbulence, and disruption; it introduces a turbulence diagnostic tool for leadership and explores patterns of variability across types of triggering …

Examining The Influence Of Organisational And Leadership Knowledge On Resilience During Economic Downturns-A Case Study For Sme Success, Dr. Aloma Jayasundera, Dr. Rubhesh Jha

Arab Economic and Business Journal

This study investigates how organisational and leadership knowledge impacts the resilience of Small and Medium Enterprises (SMEs) during economic downturns, focussing on a foreign-owned business processes and Information Consulting (IT) consulting company in Bahrain. This is a mixed-methods approach that integrates qualitative and quantitative data, including thematic analysis and Structural Equation Modelling (PLS-SEM). This study shows that an emphasis on external problems caused the company to disregard important internal challenges. The findings highlight the need for better crisis management and digital strategies to strengthen the organisation from within and create a better workplace culture. This study contributes new insights into …

Literature Review Of Local Culture-Based Mathematics E-Module With Islamic Values In Probability, Maya Puspita Sari, Surya Sari Faradiba

Jurnal Pendidikan Sains

This study is grounded in the need to address the limitations of probability learning that is often procedural, decontextualized, and disconnected from students’ cultural and religious values. It aims to develop a comprehensive understanding of how local cultural contexts and Islamic values can be systematically integrated into mathematics e-modules, particularly for probability learning, and to formulate structured design principles and quality indicators for their development. This paper adopts a Systematic Literature Review (SLR) approach by analyzing empirical studies published between 2020 and 2025, using a structured selection process involving identification, screening, eligibility, and inclusion stages. A total of 11 high-quality …