Samahang Pilipino is a multifaceted student organization which addresses the specific needs of Pilipinos at UCLA. Founded in 1972, Samahang Pilipino's membership has grown to over two hundred active members. Active on campus and in the community, this organization provides cultural programing, social events, educational forums, academic support, and represents the special concerns for greater commitment to our community and developing leadership skills. Awarded by Los angeles City Hall in honor of Samahang's 25 years of accomplishments. The archive is divided into 5 sections: Academic, Community, Cultural, Political, and Social. These 5 categories represent Samahang's pillars and serve as the foundation for sustaining a thriving student organization. Documentation that is presented reflects one or more of these categories. Link to Archive: http://scalar.usc.edu/works/samahang-digital-archive-/index
Despite the efforts made towards the Millennium Development Goals targets during the last decade, still millions of people across the world lack of improved access to water supply or basic sanitation. The increasing complexity of the context in which these services are delivered is not properly captured by the conventional approaches that pursue to assess water, sanitation and hygiene (WaSH) interventions. Instead, a holistic framework is required to integrate the wide range of aspects which are influencing sustainable and equitable provision of safe water and sanitation, especially to those in vulnerable situations. In this context, the WaSH Poverty Index (WaSH-PI) was adopted, as a multi-dimensional policy tool that tackles the links between access to basic services and the socio-economic drivers of poverty. Nevertheless, this approach does not fully describe the increasing interdependency of the reality. For this reason, appropriate Decision Support Systems (DSS) are required to i) inform about the results achieved in past and current interventions, and to ii) determine expected impacts of future initiatives, particularly taking into account envisaged investments to reach the targets set by the Sustainable Development Goals (SDGs). This would provide decision-makers with adequate information to define strategies and actions that are efficient, effective, and sustainable. This master thesis explores the use of object-oriented Bayesian networks (ooBn) as a powerful instrument to support project planning and monitoring, as well as targeting and prioritization. Based on WaSH-PI theoretical framework, a simple ooBn model has been developed and applied to reflect the main issues that determine access to safe water, sanitation and hygiene. A case study is presented in Kenya, where the Government launched in 2008 a national program aimed to increase the access to improved water, sanitation and hygiene in 22 of the 47 existing districts. Main impacts resulted from this initiative are assessed and compared against the initial situation. This research concludes that the proposed approach is able to accommodate the conditions at different scales, at the same time that reflects the complexities of WaSH-related issues. Additionally, this DSS represents an effective management tool to support decisionmakers to formulate informed choices between alternative actions.
Despite the efforts made towards the Millennium Development Goals targets during the last decade, still millions of people across the world lack of improved access to water supply or basic sanitation. The increasing complexity of the context in which these services are delivered is not properly captured by the conventional approaches that pursue to assess water, sanitation and hygiene (WaSH) interventions. Instead, a holistic framework is required to integrate the wide range of aspects which are influencing sustainable and equitable provision of safe water and sanitation, especially to those in vulnerable situations. In this context, the WaSH Poverty Index (WaSH-PI) was adopted, as a multi-dimensional policy tool that tackles the links between access to basic services and the socio-economic drivers of poverty. Nevertheless, this approach does not fully describe the increasing interdependency of the reality. For this reason, appropriate Decision Support Systems (DSS) are required to i) inform about the results achieved in past and current interventions, and to ii) determine expected impacts of future initiatives, particularly taking into account envisaged investments to reach the targets set by the Sustainable Development Goals (SDGs). This would provide decision-makers with adequate information to define strategies and actions that are efficient, effective, and sustainable. This master thesis explores the use of object-oriented Bayesian networks (ooBn) as a powerful instrument to support project planning and monitoring, as well as targeting and prioritization. Based on WaSH-PI theoretical framework, a simple ooBn model has been developed and applied to reflect the main issues that determine access to safe water, sanitation and hygiene. A case study is presented in Kenya, where the Government launched in 2008 a national program aimed to increase the access to improved water, sanitation and hygiene in 22 of the 47 existing districts. Main impacts resulted from this initiative are assessed and compared against the initial situation. This research concludes that the proposed approach is able to accommodate the conditions at different scales, at the same time that reflects the complexities of WaSH-related issues. Additionally, this DSS represents an effective management tool to support decisionmakers to formulate informed choices between alternative actions.
Typically, aggregation-diffusion is modeled by parabolic equations that combine linear or nonlinear diffusion with a Fokker-Planck convection term. Under very general suitable assumptions, we prove that radial solutions of the evolution process converge asymptotically in time towards a stationary state representing the balance between the two effects. Our parabolic system is the gradient flow of an energy functional, and in fact we show that the stationary states are minimizers of a relaxed energy. Here, we study radial solutions of an aggregation-diffusion model that combines nonlinear fast diffusion with a convection term driven by the gradient of a potential, both in balls and the whole space. We show that, depending on the exponent of fast diffusion and the potential, the steady state is given by the sum of an explicit integrable function, plus a Dirac delta at the origin containing the rest of the mass of the initial datum. This splitting phenomenon is an uncommon example of blow-up in infinite time ; The authors are thankful to the anonymous referee for the detailed reading of the manuscript, and their insightful suggestions. The research of JAC and DGC was supported by the Advanced Grant Nonlocal-CPD (Nonlocal PDEs for Complex Particle Dynamics: Phase Transitions, Patterns and Synchronization) of the European Research Council Executive Agency (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 883363). JAC was partially supported by EPSRC grant number EP/T022132/1. The research of JLV was partially supported by grant PGC2018-098440-B-I00 from the Ministerio de Ciencia, Innovación y Universidades of the Spanish Government. JLV was an Honorary Professor at Univ. Complutense
Purpose Extensive empirical evidence suggests that procedural justice (PJ) and distributive justice (DJ) are key success factors for achieving durable peace negotiations. This paper aims to investigate how complexity affects these factors and the outcomes in negotiations.
Design/methodology/approach The qualitative study is based on an examination of the peace negotiations that led to the 2016 agreement between the Fuerzas Armadas Revolucionarias de Colombia – Ejército del Pueblo and the Colombian Government. Based on document analysis, the authors examined in detail how and where in the process the principles of PJ and DJ were applied. The authors then examined the implementation progress after 2016 and placed the peace process in the overall context of the Colombian conflict.
Findings The authors found that the principles of PJ and DJ were present in both the negotiation process and the agreement. The negotiations were successful and satisfactory solutions could be found for all issues. The complexity of the conflict is reflected in the limited coverage of the peace negotiations. Not all groups, interests and subconflicts could be included in the negotiations. This limits their contribution to a durable peace in Colombia. Conflicts that remain unresolved also have a negative effect on the implementation of the agreement.
Practical implications For conflict management, this implies that the negotiations should not be viewed as "one-and-done" but rather as a progressive, ongoing process. The agreement is only the nucleus for achieving total peace. It must be actively advanced and defended.
Originality/value This study offers new qualitative insights into how PJ and DJ function in negotiations. It also establishes a systematic connection between PJ and DJ and complexity, introduces the notion of coverage and, thereby, opens a new perspective on the management of conflict complexity.
Traffic signs are a key element in driver safety. Governments invest a great amount of resources in maintaining the traffic signs in good condition, for which a correct inventory is necessary. This work presents a novel method for mapping traffic signs based on data acquired with MMS (Mobile Mapping System): images and point clouds. On the one hand, images are faster to process and artificial intelligence techniques, specifically Convolutional Neural Networks, are more optimized than in point clouds. On the other hand, point clouds allow a more exact positioning than the exclusive use of images. The false positive rate per image is only 0.004. First, traffic signs are detected in the images obtained by the 360° camera of the MMS through RetinaNet and they are classified by their corresponding InceptionV3 network. The signs are then positioned in the georeferenced point cloud by means of a projection according to the pinhole model from the images. Finally, duplicate geolocalized signs detected in multiple images are filtered. The method has been tested in two real case studies with 214 images, where 89.7% of the signals have been correctly detected, of which 92.5% have been correctly classified and 97.5% have been located with an error of less than 0.5 m. This sequence, which combines images to detection–classification, and point clouds to geo-referencing, in this order, optimizes processing time and allows this method to be included in a company's production process. The method is conducted automatically and takes advantage of the strengths of each data type. ; Xunta de Galicia | Ref. ED481B-2019-061 ; Xunta de Galicia | Ref. ED481D 2019/020 ; Xunta de Galicia | Ref. ED431C 2016-038
Traffic signs are a key element in driver safety. Governments invest a great amount of resources in maintaining the traffic signs in good condition, for which a correct inventory is necessary. This work presents a novel method for mapping traffic signs based on data acquired with MMS (Mobile Mapping System): images and point clouds. On the one hand, images are faster to process and artificial intelligence techniques, specifically Convolutional Neural Networks, are more optimized than in point clouds. On the other hand, point clouds allow a more exact positioning than the exclusive use of images. The false positive rate per image is only 0.004. First, traffic signs are detected in the images obtained by the 360° camera of the MMS through RetinaNet and they are classified by their corresponding InceptionV3 network. The signs are then positioned in the georeferenced point cloud by means of a projection according to the pinhole model from the images. Finally, duplicate geolocalized signs detected in multiple images are filtered. The method has been tested in two real case studies with 214 images, where 89.7% of the signals have been correctly detected, of which 92.5% have been correctly classified and 97.5% have been located with an error of less than 0.5 m. This sequence, which combines images to detection–classification, and point clouds to geo-referencing, in this order, optimizes processing time and allows this method to be included in a company's production process. The method is conducted automatically and takes advantage of the strengths of each data type. ; Xunta de Galicia | Ref. ED481B-2019-061 ; Xunta de Galicia | Ref. ED481D 2019/020 ; Xunta de Galicia | Ref. ED431C 2016-038
Verticillium wilt, caused by the pathogen Verticillium dahliae, is extremely devastating to olive trees (Olea europea). Currently, no successful control measure is available against it. The objective of this work was to evaluate the antifungal activity of Bacillus velezensis XT1, a well-characterized salt-tolerant biocontrol strain, against the highly virulent defoliating V. dahliae V024. In vitro, strain XT1 showed to reduce fungal mycelium from 34 to 100%, depending on if the assay was conducted with the supernatant, volatile compounds, lipopeptides or whole bacterial culture. In preventive treatments, when applied directly on young olive trees, it reduced Verticillium incidence rate and percentage of severity by 54 and ~80%, respectively. It increased polyphenol oxidase (PPO) activity by 395%, indicating an enhancement of disease resistance in plant tissues, and it decreased by 20.2% the number of fungal microsclerotia in soil. In adult infected trees, palliative inoculation of strain XT1 in the soil resulted in a reduction in Verticillium symptom severity by ~63%. Strain XT1 is biosafe, stable in soil and able to colonize olive roots endophytically. All the traits described above make B. velezensis XT1 a promising alternative to be used in agriculture for the management of Verticillium wilt. ; Xtrem Biotech S.L ; European Union SME Instrument XTOnE-774657 ; Spanish Ministry of Economy and Competitiveness SNEO-20161037E ; Spanish Government CGL2011-25748 ; Spanish Ministry of Industry, Trade and Tourism (project VertiSOLUTION) ; Ramon y Cajal program from the Ministry of Economy and Competitiveness RYC-2014-15532 ; CEI-BioTic grant of the BioTic Campus of International Excellence CAEP2-46 ; Ministry of Economy and Competitiveness DI-14-06868
This report presents the outcome of the joint work of PhD students and senior researchers working with DNA-based biodiversity assessment approaches with the goal to facilitate others the access to definitions and explanations about novel DNA-based methods. The work was performed during a PhD course (SLU PNS0169) at the Swedish University of Agricultural Sciences (SLU) in Uppsala, Sweden. The course was co-organized by the EU COST research network DNAqua-Net and the SLU Research Schools Focus on Soils and Water (FoSW) and Ecology - basics and applications. DNAqua-Net (COST Action CA15219, 2016-2020) is a network connecting researchers, water managers, politicians and other stakeholders with the aim to develop new genetic tools for bioassessment of aquatic ecosystems in Europe and beyond. The PhD course offered a comprehensive overview of the paradigm shift from traditional morphology-based species identification to novel identification approaches based on molecular markers. We covered the use of molecular tools in both basic research and applied use with a focus on aquatic ecosystem assessment, from species collection to the use of diversity in environmental legislation. The focus of the course was on DNA (meta)barcoding and aquatic organisms. The knowledge gained was shared with the general public by creating Wikipedia pages and through this collaborative Open Access publication, co-authored by all course participants.
