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Articles 54841 - 54870 of 5150696
Full-Text Articles in Entire DC Network
El Calor Del Sueño, Flor Elizabeth Cruz De León
Mi Muerte En Sueños, Aiti Guadalupe Lin López
Karelia: Recolectora De Cadáveres, Luis Daniel Abrego Pineda
Karelia: Recolectora De Cadáveres, Luis Daniel Abrego Pineda
Cuaderna Vía
No abstract provided.
Poemas, Pablo Salmerón Corraliza
Se Oye El Preludio En Mi Menor De Chopin Y Tres Poemas, Jade Izel Martínez Díaz
Se Oye El Preludio En Mi Menor De Chopin Y Tres Poemas, Jade Izel Martínez Díaz
Cuaderna Vía
No abstract provided.
Un Desprotegido Reino (Fragmentos), Gustavo Ruiz Pascacio
Un Desprotegido Reino (Fragmentos), Gustavo Ruiz Pascacio
Cuaderna Vía
No abstract provided.
Miriam Y Cefas, Harby Erubiel Camacho Avendaño
In Nomine Vicius (Fragmentos), Yolanda Gómez Fuentes
In Nomine Vicius (Fragmentos), Yolanda Gómez Fuentes
Cuaderna Vía
No abstract provided.
Editorial, The Cuaderna Vía Editors
Table Of Contents, The Cuaderna Vía Editors
Full Issue, The Cuaderna Vía Editors
Temperature And College Life, Porsha Purkiss, Quiniyah Shumpert, Olivia Lane
Temperature And College Life, Porsha Purkiss, Quiniyah Shumpert, Olivia Lane
Scholars Week
Temperature and College Life
Absenteeism in college students can be caused by a variety of factors ranging from personal attitudes to environmental factors. Considering that, on average, American college students spend over $20,000 per semester on tuition, absenteeism is unlikely to be random (Barragan Torres, 2025). This study aims to explore how climate, mental health, socioeconomic status, and basic demographic information correlate with academic attendance, with an overall focus on outdoor temperature. Research observes that temperature is a key factor of absenteeism, determining that many students are incentivized to skip class if the temperature is warm enough for leisure activities …
Using The Second-Generation Environmental Sample Processor To Provide Near Real-Time Observations Of Harmful Algae And Assess Biodiversity And Ecosystem Change, Stephanie K. Moore, Nicolaus G. Adams, John B. Mickett, Christina M. Mikulski, Nicolas Michel-Hart, James M. Birch, Brent Roman, Jan A. Newton
Using The Second-Generation Environmental Sample Processor To Provide Near Real-Time Observations Of Harmful Algae And Assess Biodiversity And Ecosystem Change, Stephanie K. Moore, Nicolaus G. Adams, John B. Mickett, Christina M. Mikulski, Nicolas Michel-Hart, James M. Birch, Brent Roman, Jan A. Newton
Benefits of Ocean Observing Catalog (BOOC)
The second-generation Environmental Sample Processor (2G-ESP) is a sophisticated autonomous sensor platform and a key component of offshore observing efforts designed to mitigate the societal impacts of harmful algal blooms (HABs) in the Pacific Northwest. Deployed as part of a moored observatory, the 2G-ESP generates near real-time data on HAB organisms and the biotoxin domoic acid, providing critical HAB early warning and directly informing HAB forecasts and fisheries management decisions. In addition, the platform’s capacity to archive environmental DNA enables retrospective analyses of biodiversity and ecosystem change. These capabilities facilitate interdisciplinary scientific collaboration and information sharing, ultimately enhancing our collective …
The Evasive Epidemic Of Missing Black Children, Trinity D. Garlick
The Evasive Epidemic Of Missing Black Children, Trinity D. Garlick
Criminal Law Society Blog
The Evasive Epidemic of Missing Black Children” brings to light the disproportionately low amount of media support for missing Black Children. It draws on examples of missing Black Children, like Adam Walsh and other Atlanta Black children, to illustrate how Black children have gone ignored by the public for too long. It discusses factors such as failure of state legislatures, lack of media exposure, unfair and racial fixed labels, and law enforcement discretionary conduct, as the leading drivers of the epidemic of missing Black children. This Article then dives into efforts to reform the American system to adequately address when …
Challenges And Best Practices Of Regional Innovation Ecosystems, Mahnaz Asgari Sooran
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 …
Introducing Gridtrees For Streaming, Scalable Hierarchical Data Visualization, Nathan Tibbetts
Introducing Gridtrees For Streaming, Scalable Hierarchical Data Visualization, Nathan Tibbetts
Miners Solving for Tomorrow Research Conference
File browsing in the consumer sphere has seen very little advancement in recent years, although attempts have been made to improve upon it. With the goal of multi-level visual file browsing in mind, we present a prototype GridTree, a dynamic, recursive, stable, spatial layout data structure based on subdividing grids, represented as a hierarchy of maps whose granularity increases with depth. We motivate this work with characteristics we have identified as important for viability of a multi-level file-browser, which have become our design goals. We touch on the underlying logic of a GridTree and identify its complexity. We briefly discuss …
Simulating Thermal Diffusion Through Image-Derived Microstructures Of Ceramic Matrix Composites, Matik Heskin
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 …
Thermal Mirage: Towards Robust Thermal Perception Via Gan-Guided Diffusion, Nuzaer Omar
Thermal Mirage: Towards Robust Thermal Perception Via Gan-Guided Diffusion, Nuzaer Omar
Miners Solving for Tomorrow Research Conference
Thermal object detection systems are critical for safety sensitive applications due to their reliability under adverse conditions. However, existing robustness evaluations in thermal domain primarily focuses on physical or sensor-level perturbations, overlooking vulnerabilities from semantically realistic scene and object manipulations. We introduce Thermal Mirage, a generative framework that leverages GAN-guided diffusion to expose weaknesses in thermal detectors through controlled object and context level perturbations. Our approach learns class-conditional thermal priors via a GAN and uses diffusion to transform object appearances into ambiguous or low-saliency patterns. Simultaneously, a context module degrades scene conditions by simulating harsher night environments. Integrated with a …
Human Intention Prediction Using Cnn And Lstm Networks In Physical Human–Robot Interactions, Khosro Ghorbani Zadeh
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 …
Ai-Driven Frameworks For Mitigating Rockfall Hazards, Unstable Ground Condition And Improving Safety In Underground Mine Through Thermal Imaging, Akhrorbek Narmatov
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
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.
Harnessing Wavefront Shaping Control For Sensing Applications, Pablo Jara
Harnessing Wavefront Shaping Control For Sensing Applications, Pablo Jara
Miners Solving for Tomorrow Research Conference
Diffuse optical tomography (DOT) and functional near-infrared spectroscopy (fNIRS) enable deep, non-invasive sensing in biological tissue but are fundamentally limited by the photon budget - most injected light is lost to scattering before reaching the detector. Wavefront shaping (WFS) can enhance signal strength inside scattering media via interference, but the conventional diffusion-based sensitivity model breaks down under coherent illumination. We develop a microscopic theory of optical sensitivity that captures interference effects neglected by diffusion theory. We prove analytically that the microscopic and diffusive descriptions coincide under random illumination and identify WFS strategies that enhance sensitivity beyond this limit. The maximum …
Variational Data Assimilation With Steepest Descent Method For Coupled Time-Dependent Stokes-Darcy Model With Bjsj Interface Condition, Yafang Hei
Miners Solving for Tomorrow Research Conference
Variational data assimilation (VDA) determines the initial condition of a dynamical system by minimizing the mismatch between model predictions and observed data. This work studies VDA for the time-dependent Stokes–Darcy system with the BJSJ interface condition. The problem is formulated as a PDE-constrained optimization problem, and the first-order optimality system is derived using the Gâteaux derivative and adjoint variables. A steepest descent method is applied for efficient computation. Spatial and temporal discretizations are carried out using the finite element method and backward Euler scheme, respectively. Numerical results confirm accuracy and convergence.
Dispersive Shock And Rogue Waves In Two-Dimensional Quantum Droplets, Farhana Bristy
Dispersive Shock And Rogue Waves In Two-Dimensional Quantum Droplets, Farhana Bristy
Miners Solving for Tomorrow Research Conference
Quantum droplets, are liquid type configurations stabilized by the balance between attractive mean-field interactions and repulsive quantum fluctuations. They provide highly flexible platforms for the quantum simulation of hydrodynamic phenomena using ultracold gases. Here, we explore the nonlinear quantum dynamics of two-dimensional quantum droplets under Riemann initial conditions. The steepness of the latter facilitates the emergence of radially symmetric dispersive shock waves (DSWs) when quantum fluctuations dominate. In particular, the ensuing DSWs travel from the potential edges toward the center where they collide and through their interference high amplitude spatially localized rogue wave structures emerge. In contrast, tuning the interactions …
Distributed Control Plane For Cross-Silo Federated Learning, Rabin Pandey
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
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 …
Toward Sustainable 3d Printable Cementitious Materials: Low-Carbon Design With Fiber Reinforcement, Nima Mahmoudzadeh Vaziri
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 …
Breath-Based Detection Of Liver Cancer Biomarkers Using An Swcnt-Fet Nanobiosensor: Quantumatk, Mohamed Mohieb Rashdan
Breath-Based Detection Of Liver Cancer Biomarkers Using An Swcnt-Fet Nanobiosensor: Quantumatk, Mohamed Mohieb Rashdan
Thesis/ Dissertation Defenses
There are still no tests to detect liver cancer in the early stages because it is a slow-growing and invasive type.
This study describes the use of a single-walled carbon nanotube-based field-effect transistor (SWCNT-FET) whose ability to detect hexanal, a volatile organic compound (VOC) found to be elevated in liver cancer, has been demonstrated through direct measurements from exhaled breath. The device is designed using QuantumATK with the semi-empirical Extended Hückel Hamiltonian framework in non-equilibrium Green’s function (NEGF) which shows realistic contact physics by using metallic SWCNT electrodes instead of common metal films. Through the analysis of two zigzag channels …
Against The Coloniality Of Sport For Development And Peace (Sdp), Isra Shahid Iqbal
Against The Coloniality Of Sport For Development And Peace (Sdp), Isra Shahid Iqbal
Journal of Global South Sport Studies
This paper critically investigates how historical colonial practices and capitalist structures continue to influence the roles, relationships, and spaces related to gender and race within Sport for Development (SDP) initiatives in Global South contexts. While sport is commonly approached as an avenue to promote positive youth development and post-conflict reconstruction, these discourses often overlook how colonial capitalist imperatives are perpetuated through sport, influencing gender and race hierarchies, oppressive relations, and the direct “Othering” of actors in Global South contexts (Samie et al., 2015; Oxford, 2017). Indeed, SDP initiatives are not immune from capitalist and colonial imperatives nor the racial and …
Leveraging Artificial Intelligence For Transformative Education: Challenges And Recommendations, Papia Bawa
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 …