Swiping Your Life Away Failing to find love through Dating Apps

This essay focuses on examining the dating experience and interactions in the age of digital technology, specifically where social disempowered users of dating applications tend to reinforce systemic social oppression. This research draws from literature about communication ethics, critical theory studies, digital media studies and includes personal observations and experiences. Even though some apps have allowed minorities; the LGBTQ community, people of color (POC) and other groups, to interact in a platform where they share common interests, there are still some dating apps which are more mainstream. Dating within the same platform where ethical communication and intent has been swayed to a hook up culture online where people run high risks of safety and damage communication ties with other potential partners. Through meeting with strangers, the potential for physical abuse rises and communication strains are at a high rate through the use of dating apps. Besides the communication and personal risks aspects that face disenfranchised communities, I also highlight in this paper the dangers of safety and privacy issues associated with location- based geosocial networking smartphone applications also known as “GSN apps” (Rice et al 1) and the ethical implications of data mining. My research process includes peer review articles that address angles of experience and risk from different minority groups as well as the general public. I examine studies about particular apps such as Grindr, Tinder, Chispa and Bumble where the authors highlight some of the dangers associated with data mining and data sharing by the use of GSN apps. I also include the voices of participants, highlighting their experiences while using the given dating application. This essay highlights how systems of oppression such - racism, sexism, classism and misogyny have carried over into the digital age, where; POC and the LGBT community have been victims of discrimination based on sexual orientation, stereotypes and assumptions about ethnicity. During a three-week period, I conducted interviews and a focus group with college students, including POC and LGBT community members in California, about their experiences using dating apps such as, Tinder, Grindr, Bumble and Chispa. The insight from interviews, plus my observation and articulation with recent scholar work create the foundation for this study. Growing up in the age of technology where the use of dating apps has grown over the years I wanted to understand its purpose in the college sphere, I began to indulge in the use of dating apps and engaged in conversations with friends and peers about the use of a dating app in hopes of creating connections. These conversations sparked my interest in dating apps and the way they are used by adults and young adults, specifically in a college campus while thinking about the implications of data collected by dating app companies from its users

A Security Monitoring Framework For Virtualization Based HEP Infrastructures

High Energy Physics (HEP) distributed computing infrastructures require automatic tools to monitor, analyze and react to potential security incidents. These tools should collect and inspect data such as resource consumption, logs and sequence of system calls for detecting anomalies that indicate the presence of a malicious agent. They should also be able to perform automated reactions to attacks without administrator intervention. We describe a novel framework that accomplishes these requirements, with a proof of concept implementation for the ALICE experiment at CERN. We show how we achieve a fully virtualized environment that improves the security by isolating services and Jobs without a significant performance impact. We also describe a collected dataset for Machine Learning based Intrusion Prevention and Detection Systems on Grid computing. This dataset is composed of resource consumption measurements (such as CPU, RAM and network traffic), logfiles from operating system services, and system call data collected from production Jobs running in an ALICE Grid test site and a big set of malware. This malware was collected from security research sites. Based on this dataset, we will proceed to develop Machine Learning algorithms able to detect malicious Jobs.Comment: Proceedings of the 22nd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2016, 10-14 October 2016, San Francisco. Submitted to Journal of Physics: Conference Series (JPCS

Two-zero textures for Dirac Neutrinos

We review the two-zero mass matrix textures approach for Dirac neutrinos with the most recent global fit in the oscillation parameters. We found that three of the 15 possible textures are compatible with current experimental data, while the remaining two-zero textures are ruled out. Two textures are consistent with the neutrino masses' normal hierarchy and are CP-conserving. At the same time, the other one is compatible with both mass orderings and allows for CP violation. We also present the correlations between the oscillation parameters for the allowed two-zero textures.Comment: 8 pages, 4 figure

Measurement driven quantum evolution

We study the problem of mapping an unknown mixed quantum state onto a known pure state without the use of unitary transformations. This is achieved with the help of sequential measurements of two non-commuting observables only. We show that the overall success probability is maximized in the case of measuring two observables whose eigenstates define mutually unbiased bases. We find that for this optimal case the success probability quickly converges to unity as the number of measurement processes increases and that it is almost independent of the initial state. In particular, we show that to guarantee a success probability close to one the number of consecutive measurements must be larger than the dimension of the Hilbert space. We connect these results to quantum copying, quantum deleting and entanglement generation.Comment: 7 pages, 1 figur

Changes in Crude Protein and Fiber Contents of Small Grain Cereals for Forage over Time

Oat, triticale, wheat and barley are small grain cereals used as forage in many temperate Mexican regions. The objective was to determine crude protein and van Soest fiber contents of these forages cut at 80, 96, 108, 121, 138 and 153 days after seeding. Cultivars used were: Chihuahua (OC) for oat; Arne (TA), Bicentenario (TB) and Siglo XXI (TS) for triticale; Saturno (WS) for wheat; and San Marcos (BSM) for barley. Experiment was under greenhouse conditions from November 2015 to May 2016. Crude protein (CP), neutral (NDF) and acid (ADF) detergents fibers were determined on the forage harvested at each time. Statistical analysis was by linear regression with cultivar as a dummy variable (R2= 0.5843 to 0.6861), response variables were CP, NDF and ADF contents over days after seeding (R2≥ 0.7693), the model included first grade interaction. Models developed were compared based on the slopes calculated. First grade interaction was significant (p\u3c 0.05) in CP due to the pattern change in TS, and in NDF due to the pattern change in OC and in ADF due to the pattern change in TA. So that, individual models and coefficient confident intervals were developed for each species and cultivar to compare them and to declare similarities or differences at p\u3c 0.05. Overall, CP decreased (p\u3e 0.05) from 0.11 to 0.39; while NDF and ADF increased (p\u3e 0.05) from 0.60 to 1.10, and from 0.20 to 0.83 percentage units day-1 respectively. It was concluded that crude protein, neutral and acid detergent fiber contents in small grain cereals are not dependent on harvesting time when measured at development stages close to physiological maturity