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Developing Peace Leadership: Lessons from the Peace Practice Alliance
No full textIn 2020, Euphrates Institute piloted the Peace Practice Alliance (PPA), a virtual six-month program that brings together an international cohort of peacebuilders to learn peace leadership theories and develop related skills and practices. The program framework is based on integral peace leadership, which focuses on four interrelated areas of Innerwork, Knowledge, Community, and Environment. As part of an emergent field, limited research has documented the application of integral peace leadership in peacebuilder training and development programs. This paper, therefore, examines the pilot PPA program to understand the ways in which an online, global peace leadership training program can support the development of community peace leaders. Findings from interviews with 14 of the program’s first cohort of 18 peace leaders revealed that the PPA supported their development through the content of the curriculum, the creation of a strong learning community, and the dual focus on theory and practice. This paper concludes with suggestions for further improvement, including additional spaces for participant interaction and experiential learning and the creation of further training and development opportunities
Carbon Restoration Potential on Global Land Under Water Resource Constraints
Get PDFEcosystem restoration is a critical nature-based solution to mitigate climate change. However, the carbon sequestration potential of restoration, defined as the maximum achievable carbon storage, has likely been overestimated because previous studies have not adequately accounted for the competition between ecosystem water demands for maximizing carbon sequestration and human water needs. Here we used a comprehensive process-based model combined with extensive land-use data and evaporation recycling accounting for land–atmosphere feedback to estimate the water requirements associated with ecosystem restoration. We found that achieving the carbon sequestration potential of restoration would significantly reduce global water availability per capita by 26%, posing considerable risks to water security in water-stressed and highly populated regions. If human water use is safeguarded, the achievable carbon sequestration potential would be reduced by a third (from 396 PgC to 270 PgC). Brazil, the United States and Russia have the largest achievable potentials. Future projections accounting for changes in climate, atmospheric CO2, land use and human population under the shared socioeconomic pathway (SSP) scenarios SSP119, SSP245 and SSP585 suggest an increase in this achievable potential to 274–302 PgC by the end of the century, with China expected to have the largest potential. Our findings provide a nuanced understanding of the trade-offs and synergies between carbon sequestration goals and water security, offering an empirical framework to guide the sustainable implementation of ecosystem restoration strategies
Frames and Spaces for Distributive Quasi Relation Algebras and Distributive Involutive FL-Algebras
No full textAnalogous to atom structures for relation algebras, we define partially ordered frames and prove they are duals for complete perfect distributive quasi relation algebras and distributive involutive FL-algebras. We then extend this dual representation to all algebras and their corresponding frames with a Priestley topology.
For relation algebras up to size 16 it has been determined which algebras are representable by binary relations. We compute all finite distributive quasi relation algebras up to 8 elements and provide representations for some of them
Enhanced Lithological Mapping in Arid Crystalline Regions Using Explainable AI and Multi-spectral Remote Sensing Data
Get PDFLithological classification is essential for understanding the spatial distribution of rocks, especially in arid crystalline areas. Artificial intelligence (AI) recent advancements with multi-spectral satellite imagery have been utilized to enhance lithological mapping in these areas. Here we employed different AI models namely, Support Vector Machine (SVM), Random Forest Classification (RFC), Logistic Regression, XGBoost, and K-nearest neighbors (KNN) for lithological mapping. This was followed by the application of explainable AI (XAI) for lithological discrimination (LD) which is still not widely explored. Based on the highest accuracy and F1 score of the previously mentioned models, RFC model outperformed all of them, and hence, it was integrated with XAI, using the SHapley Additive exPlanations (SHAP) method. This approach successfully identified critical multi-spectral features for LD in arid crystalline zones when applied on the Landsat-8, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and SRTM-DEM datasets covering the Hammash and the Wadi Fatimah areas in Egypt and the Kingdom of Saudi Arabia, respectively. Field validation in the Hammash area confirmed the RFC model\u27s efficacy, achieving a satisfactory 94% overall accuracy for 18 features. SHAP was able to identify the top ten features for proper LD over the Hammash area with 90.3% accuracy despite the complex nature of the ophiolitic mélange. For validation purposes, RCF was then utilized in the Wadi Fatimah region, using only the top 10 critical features rendered from the SHAP analysis. It performed well and had 93% accuracy. Notably, XAI/SHAP results indicated that elevation data, Landsat-8\u27s Green Band (B3), and the two ASTER SWIR bands (B5 and B6) were essential and significant for identifying island arc rocks. Moreover, the SHAP model effectively delineated complex mélange matrices, primarily using ASTER SWIR band (B8). Our findings highlight the successful combination of RFC with XAI for LD and its potential utilization in similar arid crystalline environments worldwide
2024 2nd Place Winner: Heather Ulwick, “What\u27s Your Hip-Hop Story? How Authenticity has Simultaneously Fought and Imposed the Commercialization of Rap”
No full textPictured is 2024 second-place winner Heather Ulwick (center, holding the certificate), with (left to right) Taylor Greene (Chair of Research and Instructional Services) and Dr. Kevin Ross (contest co-sponsor and Dean of the Leatherby Libraries).https://digitalcommons.chapman.edu/undergraduateresearchprize_images/1029/thumbnail.jp
2024 1st Place Winner: Gabriella Dauber, “Examining Students’ Perception of & Experiences in STEM Course Office Hours”
No full textPictured is 2024 first-place winner Gabriella Dauber (second from right, holding the certificate), with (left to right) Taylor Greene (Chair of Research and Instructional Services), Dr. Jeremy Hsu (Assistant Professor of Biology) and Dr. Kevin Ross (contest co-sponsor and Dean of the Leatherby Libraries).https://digitalcommons.chapman.edu/undergraduateresearchprize_images/1028/thumbnail.jp
Seasonal Dynamics in Land Surface Temperature in Response to Land Use Land Cover Changes Using Google Earth Engine
Get PDFChanges in land use and land cover (LULC) are critical for evaluating global spatiotemporal trends, especially regarding climate change and urbanization. This study investigates the dynamics of Landsat surface temperature (LST) in response to LULC changes and their effects on the seasonal microclimate in Kasur District, Pakistan. Using the Google Earth Engine platform, we employed a random forest algorithm to detect LULC changes (cropland, forest, built-up, fallow, barren, and water) and analyze seasonal spectral indices from Landsat imagery for 1988, 2002, and 2022. Significant LULC changes were observed, including a 9.8% increase in built-up areas, a 4.2% decrease in cropland, and a 1.4% decrease in forested areas, linked to urban heat island effects and population growth. Additionally, there was a 2.7% increase in fallow and open land, contributing to the district\u27s impervious surface area. Significant correlations ( p \u3c 0.001) were found between LST and spectral indices—normalized difference vegetation index, enhanced vegetation index, and normalized difference built index (NDBI)—ranging from 0.7 to 0.8 in both winter and summer. In summer, the maximum LST increased from 43 °C in 1988 to 44 °C in 2002, with a linear correlation ( R ²) increase from 0.57 to 0.75 and a polynomial correlation ( R ²) increase from 0.63 to 0.76 with NDBI from 1988 to 2022. Understanding these dynamics is crucial as LULC changes and the resulting temperature variations have significant implications for local climate, agriculture, and human health. This study underscores the need for effective LULC policies to mitigate impacts, protect vegetation cover, and ensure sustainable land management. These findings provide valuable insights for policymakers and urban planners aiming to balance development with environmental sustainability
Comment on \u27From Counterportation to Local Wormholes\u27
Get PDFHatim Salih discovered a method for transferring a quantum state with no particles present in the transmission channel, which he named counterportation. Recently (Salih 2023 Quantum Sci. Technol.8 025016), he presented a feasible procedure for its implementation. The modification of the protocol by Aharonov and Vaidman, adopted by Salih, justifies the claim that no photons were present in the transmission channel during counterportation. We argue, however, that there is an error in this paper. The analysis of a simplified protocol, which questions the validity of the two-state vector formalism description of the photon presence in the communication channel, is incorrect
Spatial Analyses on Pre-earthquake Ionospheric Anomalies and Magnetic Storms Observed by China Seismo-electromagnetic Satellite in August 2018
Get PDFThe China Seismo-Electromagnetic Satellite (CSES), with a sun-synchronous orbit at 507 km altitude, was launched on 2 February 2018 to investigate pre-earthquake ionospheric anomalies (PEIAs) and ionospheric space weather. The CSES probes manifest longitudinal features of four-peak plasma density and three plasma depletions in the equatorial/low-latitudes as well as mid-latitude troughs. CSES plasma and the total electron content (TEC) of the global ionosphere map (GIM) are used to study PEIAs associated with a destructive M7.0 earthquake and its followed M6.5 and M6.3/M6.9 earthquakes in Lombok, Indonesia, on 5, 17, and 19 August 2018, respectively, as well as to examine ionospheric disturbances induced by an intense storm with the Dst index of − 175 nT on 26 August 2018. Anomalous increases (decreases) in the GIM TEC and CSES plasma density (temperature) frequently appear specifically over the epicenter days 1–5 before the M7.0 earthquake and followed earthquakes, when the geomagnetic conditions of these PEIA periods are relatively quiet, Dst: − 37 to 19 nT. In contrast, TEC and CSES plasma parameter anomalies occur globally in the southern hemisphere during the storm days of 26–28 August 2018. The CSES ion velocity shows that the electric fields of PEIAs associated with the M7.0 earthquake are 0.21/0.06 mV/m eastward and 0.11/0.10 mV/m downward at post-midnight/post-noon on 1–3 August 2018, while the penetration electric fields during the storm periods of 26–28 August 2018 are 0.17/0.45 mV/m westward/downward at post-midnight of 02:00 LT and 0.26/0.26 mV/m eastward/upward at post-noon of 14:00 LT. Spatial analyses on CSES plasma discriminate PEIAs from global effects and locate the epicenter of possible forthcoming large earthquakes. CSES ion velocities are useful to derive PEIA- and storm-related electric fields in the ionosphere
