Surveying the Scope of the SU(2)_L Scalar Septet Sector

Extending the Standard Model by adding a scalar field transforming as a septet under $SU(2)_L$ preserves the $\rho$ parameter at tree level and can satisfy experimental constraints on the electroweak parameters $S$ and $T$. This work presents the first fully general phenomenological study of such an extension. We examine constraints on the septet model couplings based on electroweak and Higgs observables, and use LHC searches for new physics to bound the mass of the septet to be above $\sim 400$ GeV at a $95\%$ CL.Comment: pdfLateX, 17 pages, 6 figures, reference added. Version published in JHE

Dirac Triplet Extension of the MSSM

In this paper we explore extensions of the Minimal Supersymmetric Standard Model involving two $SU(2)_L$ triplet chiral superfields that share a superpotential Dirac mass yet only one of which couples to the Higgs fields. This choice is motivated by recent work using two singlet superfields with the same superpotential requirements. We find that, as in the singlet case, the Higgs mass in the triplet extension can easily be raised to $125\,\text{GeV}$ without introducing large fine-tuning. For triplets that carry hypercharge, the regions of least fine tuning are characterized by small contributions to the $\mathcal T$ parameter, and light stop squarks, $m_{\tilde t_1} \sim 300-450\,\text{GeV}$; the latter is a result of the $\tan\beta$ dependence of the triplet contribution to the Higgs mass. Despite such light stop masses, these models are viable provided the stop-electroweakino spectrum is sufficiently compressed.Comment: 26 pages, 4 figure

Exploring rationality of self awareness in social networking for logical modeling of unintentional insiders

Unawareness of privacy risks together with approval seeking motivations make humans enter too much detail into the likes of Facebook, Twitter, and Instagram. To test whether the rationality principle applies, we construct a tool that shows to a user what is known publicly on social networking sites about her. In our experiment, we check whether this revelation changes human behaviour. To extrapolate and generalize, we use the insights gained by practical experimentation. Unaware users can become targeted by attackers. They then become unintentional insid- ers. We demonstrate this by extending the Isabelle Insider framework to accommodate a formal model of unintentional insiders, an open problem with long standing

Programming for energy monitoring/display system in multicolor lidar system research

The Z80 microprocessor based computer program that directs and controls the operation of the six channel energy monitoring/display system that is a part of the NASA Multipurpose Airborne Differential Absorption Lidar (DIAL) system is described. The program is written in the Z80 assembly language and is located on EPROM memories. All source and assembled listings of the main program, five subroutines, and two service routines along with flow charts and memory maps are included. A combinational block diagram shows the interfacing (including port addresses) between the six power sensors, displays, front panel controls, the main general purpose minicomputer, and this dedicated microcomputer system

Exploring rationality of self awareness in social networking for logical modeling of unintentional insiders

Unawareness of privacy risks together with approval seeking motivations make humans enter too much detail into the likes of Facebook, Twitter, and Instagram. To test whether the rationality principle applies, we construct a tool that shows to a user what is known publicly on social networking sites about her. In our experiment, we check whether this revelation changes human behaviour. To extrapolate and generalize, we use the insights gained by practical experimentation. Unaware users can become targeted by attackers. They then become unintentional insid- ers. We demonstrate this by extending the Isabelle Insider framework to accommodate a formal model of unintentional insiders, an open problem with long standing

Toxoplasma gondii infection in workers occupationally exposed to unwashed raw fruits and vegetables: a case control seroprevalence study

<p>Abstract</p> <p>Background</p> <p>Through a case control seroprevalence study, we sought to determine the association of <it>Toxoplasma gondii </it>infection with occupational exposure to unwashed raw fruits and vegetables.</p> <p>Methods</p> <p>Subjects, numbering 200, who worked growing or selling fruits and vegetables, and 400 control subjects matched by age, gender, and residence were examined by enzyme immunoassays for the presence of anti-<it>Toxoplasma </it>IgG and IgM antibodies. Socio-demographic, clinical, and behavioral characteristics from the study subjects were obtained.</p> <p>Results</p> <p>Of the 200 fruit and vegetable workers, 15 (7.5%) of whom, and 31 (7.8%) of the 400 controls were positive for anti-<it>Toxoplasma </it>IgG antibodies (<it>P </it>= 0.96). Anti-<it>Toxoplasma </it>IgM antibodies were found in 2 (1%) of the fruit workers and in 11 (2.8%) of the control subjects (<it>P </it>= 0.23). Seroprevalence of <it>Toxoplasma </it>antibodies increased with age (<it>P </it>= 0.0004). In addition, seropositivity to <it>Toxoplasma </it>was associated with ill status (<it>P </it>= 0.04), chronic tonsillitis (<it>P </it>= 0.03), and reflex impairment (<it>P </it>= 0.03). Multivariate analysis showed that <it>Toxoplasma </it>infection was associated with consumption of raw meat (OR = 5.77; 95% CI: 1.15-28.79; <it>P </it>= 0.03), unwashed raw fruits (OR = 2.50; 95% CI: 1.11-5.63; <it>P </it>= 0.02), and living in a house with soil floors (OR = 3.10; 95% CI: 1.22-7.88; <it>P </it>= 0.01), whereas <it>Toxoplasma </it>infection was negatively associated with traveling abroad (OR = 0.28; 95% CI: 0.12-0.67; <it>P </it>= 0.005).</p> <p>Conclusions</p> <p>This is the first report of seroprevalence and contributing factors for <it>Toxoplasma </it>infection in workers occupationally exposed to unwashed raw fruits and vegetables, and the results may help in the design of optimal preventive measures against <it>Toxoplasma </it>infection especially in female workers at reproductive age.</p

Quark mass hierarchy in 3-3-1 models

We study the mass spectrum of the quark sector in an special type I-like model with gauge symmetry $SU(3)_c \otimes SU(3)_L \otimes U(1)_X$. By considering couplings with scalar triplets at large ($\sim TeV$) and small ($\sim GeV$) scales, we obtain specific zero-texture mass matrices for the quarks which predict three massless quarks ($u,d,s$) and three massive quarks ($c,b,t$) at the electroweak scale ($\sim$ GeV). Taking into account mixing couplings with three heavy quarks at large scales predicted by the model, the three massless quarks obtain masses at small order that depends on the inverse of the large scale. Thus, masses of the form $m_u \lesssim m_d < m_s \sim MeV$ and $m_{c,b,t} \sim GeV$ can be obtained naturally from the gauge structure of the model

Clinical Research in Occupational Therapy

The capstone project examined the role and requirements of clinical research in occupational therapy (OT) by intersecting the capstone focus areas of clinical practice and research. The overarching goal of the capstone project was to gain hands-on experience and skills associated with the different stages of clinical research, including study design, protocol development, data collection, data analysis, dissemination, program development and evaluation, and funding. The capstone goals and objectives were achieved through my participation in ongoing studies at the National Institutes of Health (NIH) Clinical Center in Bethesda, Maryland under the mentorship of Rachel Hingst, MPH, OTR/L, CPRP. Rachel Hingst serves as the mental health OT specialist within the Clinical Center and is an associate investigator on studies researching the experience and role of cooking in the health and wellbeing of underserved or at-risk groups. A supplemental data analysis component under the mentorship of Gustavo Reinoso, Ph.D., OTR/L was included in the capstone project to further my understanding of study design from a statistical perspective. Dr. Gustavo Reinoso is a renowned professor and occupational therapist with rich experience in data analysis and statistical methods, including Rasch analysis and assessment tool development. My capstone responsibilities included engaging in clinical OT sessions for clinical trial participants, advancing assigned projects, engaging with the clinical and research teams, and developing clinical scenarios for statistical analysis by future students. My participation as a capstone student at the NIH Clinical Center served to advance the research agenda of the Rehabilitation Medicine Department (RMD), assist in validating cooking as a skilled intervention for OT, and assist future students in the Nova Southeastern University research courses through resources developed

Active biopolymer networks generate scale-free but euclidean clusters

We report analytical and numerical modelling of active elastic networks, motivated by experiments on crosslinked actin networks contracted by myosin motors. Within a broad range of parameters, the motor-driven collapse of active elastic networks leads to a critical state. We show that this state is qualitatively different from that of the random percolation model. Intriguingly, it possesses both euclidean and scale-free structure with Fisher exponent smaller than $2$. Remarkably, an indistinguishable Fisher exponent and the same euclidean structure is obtained at the critical point of the random percolation model after absorbing all enclaves into their surrounding clusters. We propose that in the experiment the enclaves are absorbed due to steric interactions of network elements. We model the network collapse, taking into account the steric interactions. The model shows how the system robustly drives itself towards the critical point of the random percolation model with absorbed enclaves, in agreement with the experiment.Comment: 6 pages, 7 figure

The 4+1 Model of Data Science

Data Science is a complex and evolving field, but most agree that it can be defined as a combination of expertise drawn from three broad areascomputer science and technology, math and statistics, and domain knowledge -- with the purpose of extracting knowledge and value from data. Beyond this, the field is often defined as a series of practical activities ranging from the cleaning and wrangling of data, to its analysis and use to infer models, to the visual and rhetorical representation of results to stakeholders and decision-makers. This essay proposes a model of data science that goes beyond laundry-list definitions to get at the specific nature of data science and help distinguish it from adjacent fields such as computer science and statistics. We define data science as an interdisciplinary field comprising four broad areas of expertise: value, design, systems, and analytics. A fifth area, practice, integrates the other four in specific contexts of domain knowledge. We call this the 4+1 model of data science. Together, these areas belong to every data science project, even if they are often unconnected and siloed in the academy.Comment: 28 page