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Landlord Licensure: A Pathway to Improved Rental Housing in New Mexico
No full textOver a thousand different professions throughout the United States are subject to occupational regulations for the purpose of protecting public health, safety, and welfare. Yet, few professions are as crucial to public health, safety and welfare as the business that controls access to rental housing. The availability of rental housing is critical to the people of New Mexico due to the state’s high percentage of low-income households and the shortage of affordable housing units available in recent years. Thus, low-income renters in New Mexico are often left dealing with substandard housing conditions or paying a significant portion of their income on housing costs—or face both hardships—to avoid eviction or pro se litigation. These problems, and others, contribute to larger systemic issues like homelessness and low economic growth. Despite these issues, there are currently no regulations that require a landlord of long-term rental housing to identify themself or the rental property they own and manage in New Mexico. Thus, policymakers in New Mexico have little to no control over, or knowledge of, the landlords dictating the rental housing market. This Comment proposes a pathway to change that: landlord licensure. New regulation, which would require landlords of long-term rental housing to be licensed in New Mexico, would provide a basis for the collection of much-needed rental housing data, training programs, community outreach, proactive housing code enforcement, and other benefits. Although there are potential drawbacks, landlord licensure has real potential to significantly improve the quality of rental housing in New Mexico
Andean Epistemology, Ch’ixi, and Neutrosophic Logic
No full textThis article explores the potential of Andean epistemology—rooted in principles of complementarity (yanantin), interdependence, and indeterminacy—to enrich contemporary science and artificial intelligence (AI). By transcending binary logic through concepts like ch’ixi (simultaneous coexistence of opposites) and yanantin, Andean thought aligns with Florentin Smarandache’s neutrosophic logic, a system that formalizes truth (T), falsehood (F), and indeterminacy (I) to navigate ambiguity. Smarandache’s MultiAlism, which emphasizes the coexistence of multiple perspectives, further resonates with Andean cosmovision, offering a framework to reinterpret mythology and folklore beyond rigid dualities. Integrating these principles into AI could foster systems that better handle uncertainty, cultural context, and ethical complexity. However, current models like GPT-4 exhibit critical limitations: biases toward overestimating truth values (T) and artificially clustering indeterminacy (I ≈ 0.7), flattening nuanced concepts such as yanantin and ch’ixi. Additionally, the low semantic similarity (cosine = 0.17) between AI-generated justifications and original Andean texts reveals gaps in replicating cultural terminology and relational reasoning, underscoring the need for epistemologically grounded AI design. Future work should prioritize expanding datasets with contextualized examples—including regional variations, ritual practices, and neutrosophic scales (T, I, F)—employing advanced language models aligned with Andean epistemological annotations and integrating hybrid post processing strategies such as bilingual (Quechua/Spanish) fine-tuning and expert collaboration for culturally and technically rigorous validation. By bridging Andean philosophy with Smarandache’s neutrosophic frameworks, this research advocates for culturally inclusive AI capable of honoring pluralistic worldviews, fostering equitable knowledge systems, and advancing technologies that serve humanity and the planet holisticall
Adaptive Triangular Linguistic Neutrosophic Cubic Fuzzy Sets for College English Blended Teaching Mode Evaluation Method
No full textThis paper presents a proactive strategy that employs a multiple-criteria decision-making (MCDM) model as an evaluation tool. To assess online and offline blended teaching modes for college English, we propose an evaluation framework called CIMAS-COBRA, which integrates the Criteria Importance Assessment (CIMAS) method for determining criteria weights and the Cost Estimation, Benchmarking, and Risk Assessment (COBRA) method for ranking alternatives. Both methods operate under the Triangular Linguistic Neutrosophic Cubic Fuzzy Sets framework to handle uncertain and vague data. Seven criteria and ten alternatives are examined in this study. The Triangular Linguistic Neutrosophic Cubic Fuzzy Number approach is employed to evaluate these criteria and alternatives
Enhancing Missing Data Imputation for Migrants Data: A Neutrosophic Set-Based Machine Learning Approach
No full textThis study tackles the problem of missing data in migrant datasets by introducing a new framework that combines machine learning techniques with neutrosophic sets. These sets, which can represent uncertainty and ambiguity, are well-suited for managing the complex nature of missing information in sensitive fields like migration research. We test the effectiveness of KNN, SVM, decision tree, random forest, and Ada Boost algorithms on a migrant dataset, comparing their results using different imputation methods (mean/mode, model-based imputer (simple tree), and random values). Our research showed that our proposed approach, which used neutrosophic sets, improved imputation accuracy and strengthened model reliability. Our results underscored the potential of neutrosophic set-based machine learning for addressing missing data issues across various fields
Clear Approach to Education Quality Evaluation of Multilingual Higher Education Internationalization under Probabilistic Simplified Neutrosophic Sets for Academic Improvement
No full textAn integrated multi-criteria decision-making (MCDM) approach is used in this study to evaluate multilingual higher education internationalization. This study is the first to employ a novel combination technique that has not yet been used for corporate performance evaluation. It is based on root assessment method (RAM) and indifference threshold-based attribute ratio analysis (ITARA) methodologies. The weights of the criteria are determined using the ITARA approach, and the RAM method is used to rank the alternatives. these methods are used under the neutrosophic sets to deal with vague and uncertainty data. This study uses the Probabilistic Simplified Neutrosophic sets to overcome uncertainty issues. Three experts have evaluated the criteria and alternatives. We used seven criteria and ten alternatives to be evaluated and selected the best one
Quality Review of Computer Digital Media Art Design using Neutrosophic Logic: A Case Study
No full textEvaluating the quality of Computer Digital Media Art Design is complex because it involves both subjective artistic elements and objective technical criteria. This study uses the multi-criteria decision making (MCDM) method to deal with different criteria. Two MCDM methods are used in this study such as Preference Selection Index (PSI) Method to compute the criteria weights and the RATGOS method to rank the alternatives. These methods are used neutrosophic sets to dela with vague and uncertainty information. Eight criteria and seven alternatives are used to select the best alternatives. Four experts have evaluated these criteria and alternatives. An example is conducted to show the validation of the proposed approach. The sensitivity analysis and comparative analysis are applied in this study to show the stability of the ranks and the effectiveness of the proposed approach
2025 - Past and Future Directions for Patient-Reported Experience and Patient-Reported Outcome Assessment in Ambulatory Healthcare
No full textAnnual Joseph V. Scaletti Memorial Lecture hosted by the Clinical & Translational Science Center
Residents as Leaders: Enhancing Leadership and Teamwork in Trauma Resuscitation
No full textThis comprehensive training program successfully combines theoretical knowledge and experiential learning to prepare residents for effective trauma team leadership. Future iterations aim to expand interdisciplinary training and introduce regular simulations to reinforce skill retention and team dynamics
Empowering Guideline Searching with Guidelines Resources
No full textThis workshop presentation, Empowering Guideline Searching with Guidelines Resources, provides a comprehensive overview of major resources and effective strategies for locating clinical practice guidelines. The session introduces key platforms-including ECRI Guidelines Trust, Guideline Central, PubMed, and CINAHL-and demonstrates how to leverage professional society websites and Google search techniques to access authoritative, evidence-based guidelines. Attendees learn to compare resource features, apply advanced search filters, and ensure access to the most current recommendations for clinical decision-making. The presentation also highlights integration with HSLIC resources and support for point-of-care use.https://digitalrepository.unm.edu/hslic-posters-presentations/1185/thumbnail.jp
Mathematics in Everyday Life: Exploring Practical Applications and Real-World Impact
No full textMathematics is an essential part of daily life and influences decisions and problem-solving in various aspects of life. This study explores how mathematical concepts are embedded in daily activities such as financial management, cooking, travel planning, and technological interactions. We will show how arithmetic, algebra, geometry, and statistics are applied in real life to improve decision-making, efficiency, and productivity. Findings indicate that people with higher mathematical literacy solve problems more efficiently, especially in budgeting, as accurate calculations minimize financial mistakes and facilitate long-term financial planning. In cooking, proportional reasoning ensures the accuracy of recipes, thus providing consistent culinary results. Travel planning is made easier by calculations of time and distance, which optimize routes and save fuel. Statistical analysis helps in interpreting data trends, which is very important in areas such as health monitoring, market forecasting, and academic research. Moreover, mathematical skills improve spatial awareness in home design and construction, ensuring safety and functionality. Understanding probability supports decision-making in risk management, insurance, and gaming. In technology, algorithms based on mathematical models drive innovations from search engines to artificial intelligence applications. The study concludes that mathematical knowledge is essential for informed decision-making and resource management. Encouraging mathematical education through practical examples can bridge the gap between theoretical learning and real-worldapplication, fostering a mathematically literate society equipped to tackle complex challenges in diverse fields