Fort Lewis College

ABSTRACT Tribal Colleges and Universities (TCUs) play a critical role in Indigenous nation‐building and postsecondary access, yet faculty development within these institutions remains chronically under‐resourced and inconsistently supported. This critical literature review examines faculty development across TCUs that function primarily within the community college sector, with attention to the structural and policy conditions shaping professional growth. Drawing on peer‐reviewed scholarship, institutional data, and cross‐institutional examples, the analysis identifies persistent challenges related to chronic underfunding, faculty workload, limited professional infrastructure, and misalignment between prevailing faculty development models and the missions of Indigenous‐serving institutions. The review synthesizes evidence from 37 TCUs serving approximately 28,000 students annually and examines how faculty development is supported at institutional, consortial, and federal levels. Although TCUs receive substantially less federal funding per student than other public community colleges, the literature documents meaningful innovation in faculty development when culturally grounded approaches and sustained resources are available. Building on this synthesis, the article advances a three‐tiered framework for faculty development that distinguishes near‐term institutional strategies from mid‐ and long‐term consortial and federal actions. The framework offers practical guidance for institutional leaders, policymakers, and intermediary organizations seeking to strengthen faculty capacity while honoring tribal sovereignty, community accountability, and the teaching‐centered missions of community college‐functioning TCUs.

Abstract The DarkSide-20k dark matter direct detection experiment will employ a $${21}\,\hbox {m}^{2}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>21</mml:mn> <mml:mspace/> <mml:msup> <mml:mtext>m</mml:mtext> <mml:mn>2</mml:mn> </mml:msup> </mml:mrow> </mml:math> silicon photomultiplier (SiPM) array, instrumenting a dual-phase 50 tonnes liquid argon Time Projection Chamber (TPC). SiPMs are arranged into modular photosensors called Tiles , each integrating 24 SiPMs onto a printed circuit board (PCB) that provides signal amplification, power distribution, and a single-ended output for simplified readout. $$16$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>16</mml:mn> </mml:mrow> </mml:math> Tiles are further grouped into Photo-Detector Units (PDUs). This paper details the production of the Tiles and the Quality Assurance and Quality Control (QA-QC) protocol established to ensure their performance and uniformity. The production and QA-QC of the Tiles are carried out at Nuova Officina Assergi (NOA), an ISO-6 clean room facility at LNGS. This process includes wafer-level cryogenic characterisation, precision die attaching, wire bonding, and extensive electrical and optical validation of each Tile. The overall production yield exceeds 83.5%, matching the requirements of the DarkSide-20k production plan. These results validate the robustness of the Tile design and its suitability for operation in a cryogenic environment.

Dynamic programming accelerators (DPAs) are devices designed with an instruction set optimized for dynamic programming (DP) operations. DP is fundamental to solving complex networking problems, particularly those involving fault tolerance and routing under dynamic conditions. This paper explores the use of DPA to accelerate network resilience by implementing an optimal routing algorithm that efficiently identifies alternative paths in response to link failures. The system’s performance is evaluated by comparing DPA implementation against conventional GPU-based and CPU-based solutions. Results show that DPA provides significant performance improvements, enabling faster recovery and improved robustness in dynamic network environments.

This within-groups, repeated measures study examined differences in how accurately people with aphasia (PWA) described themes depicted in AAC displays (theme description accuracy), the types of descriptions they produced (action, naming, or combined action and naming messages), and their display preferences when viewing grids and visual scene displays (VSDs). Nineteen adults with aphasia participated in this study. Each participant viewed grids and VSDs with matched content (e.g., people, objects) presented on a computer monitor and described themes presented in each display. They then completed a display preference task. Results revealed that participants described VSDs themes correctly more often than grid themes; however, grids were described with partial correctness more often than VSDs. Additionally, both display types were described using verbs or verb phrases (action messages), more frequently than nouns or noun phrases (naming messages); however, VSDs were described using action messages more often than grids. Participants also reported greater preference for VSDs than grids. Study results support existing research that both grids and VSDs can effectively support communication for adults with aphasia; however, they may differ in their ability to represent action and naming messages. In addition, results indicate that PWA may prefer VSDs over grids.

The convolutional network is the preferred option for handling large input sizes and is commonly used in neural networks for most applications. In this experiment we demonstrate the performance of a modified convolutional neural networks (CNN) using an exponent based weight. The Exponential Convolutional Neural Network (ECNN) was tested on bacteria classification, with different model deployed on edge devices such as a Raspberry Pi and Esp32. Additionally we created a model with 3-output that can detect a specific bacteria like E. coli, aiding environmental engineers in improving efficiency. As a result, our 4-layer standard CNN model was able to achieve an accuracy of 85% for 30 bacteria strains and this 4-layer model was successfully deployed to an edge device (the Raspberry Pi 5), with model quantization using TensorFlow Lite. ECNN is having an accuracy of 68% on test set and 89% accuracy training set. This study shows the potential of deploying a CNN for bacterial detection on edge devices. Future work will be focused on improving model generalization, reducing overfitting, and improving real-time inference performance to create a more reliable and efficient system for the environment and water quality monitoring.

Leishmania donovani (LD) is a eukaryotic parasite that causes visceral leishmaniasis, which is a neglected tropical disease (NTD), in humans. During its life cycle, promastigotes produce extracellular vesicles (EVs), which can affect parasite-host interactions and modify the host immune response. Parasite-derived extracellular vesicles (EVs) act as carriers of proteins, lipids, nucleic acids, and metabolites, playing a critical role in genetic exchange and early host-parasite communication. Previous studies have shown that Leishmania EVs typically induce an M2 anti-inflammatory response in macrophages which can increase parasite infection and survival.

Surfing is a growing international industry with an increasingly diverse participant population and infrastructure that can result in positive and negative social, ecological, and economic impacts on the surfing communities. Surfers who are seeking authentic experiences may require travel to remote, rural, and economically impoverished areas. Many of these destinations have significant developmental needs that can be addressed via volunteering by surf tourists. As sustainability becomes an increasingly critical and pressing issue, more surf voluntourism organizations are emerging. Yet, there have been no studies exploring the personality traits of surf voluntourists, which could be leveraged to influence the success of the programs. This research study used the HEXACO-PI-R scale to identify personality traits of surf voluntourists that can help community and nonprofit organizations develop more effective programs for surf tourists to maximize benefits, minimize conflicts, and contribute to the sustainability of the surfing destination.