Systems and Methods for Automatic Institution Skills Optimization

An automated system and method are disclosed for the optimization of multidimensional skillsets in a hiring process. The system extracts skills from existing individuals in an organization that are then aggregated to build an entity of skills at a company or network level to identify the distribution of skills in aggregate. The method compares a specific organization to a baseline organization to determine the gaps in skills. The external market conditions and the company’s financial data are used as signals to forecast and provide the necessary staffing recommendations. The output provided is a set of job descriptions and compensation information which is integrated into any candidate matching system to reduce the overall hiring time significantly. The system and method would help identify appropriate representation of skillsets in a company and trigger manpower decisions in an objective way, with benefits to the organization in terms of business preparedness

Drosophila Bruce Can Potently Suppress Rpr- and Grim-Dependent but Not Hid-Dependent Cell Death

Bruce is a large protein (530 kDa) that contains an N-terminal baculovirus IAP repeat (BIR) and a C-terminal ubiquitin conjugation domain (E2) 1, 2. BRUCE upregulation occurs in some cancers and contributes to the resistance of these cells to DNA-damaging chemotherapeutic drugs [2]. However, it is still unknown whether Bruce inhibits apoptosis directly or instead plays some other more indirect role in mediating chemoresistance, perhaps by promoting drug export, decreasing the efficacy of DNA damage-dependent cell death signaling, or by promoting DNA repair. Here, we demonstrate, using gain-of-function and deletion alleles, that Drosophila Bruce (dBruce) can potently inhibit cell death induced by the essential Drosophila cell death activators Reaper (Rpr) and Grim but not Head involution defective (Hid). The dBruce BIR domain is not sufficient for this activity, and the E2 domain is likely required. dBruce does not promote Rpr or Grim degradation directly, but its antiapoptotic actions do require that their N termini, required for interaction with DIAP1 BIR2, be intact. dBruce does not block the activity of the apical cell death caspase Dronc or the proapoptotic Bcl-2 family member Debcl/Drob-1/dBorg-1/Dbok. Together, these results argue that dBruce can regulate cell death at a novel point

Health-care providers' perceptions, attitudes towards and recommendation practice of cervical cancer screening

In Libya, cervical cancer is ranked third as the most frequent cancer among women with early diagnosis being shown to reduce morbidity and mortality. Health-care providers can influence women's screening behaviours, and their lack of recommendations for screening can be one of the barriers that affect women's participation in screening programmes. This study aims to assess the health-care provider's perception around cervical cancer screening. In-depth, face-to-face interviews were conducted with 16 health-care providers, from both public and private sectors in Az-Zawiya city, Libya, between February and July of 2014. The interviews were recorded and transcribed, then analysed using thematic analysis. Our findings suggest that health-care providers did not provide sufficient information regarding cervical cancer screening for women who attend health-care facilities. The results highlight the role played by health-care professionals in motivating women to attend cervical cancer screening programs, and the need for health education of health-care providers to offer a precious advice regarding the screening. On the other hand, health-care providers highlighted that implementation of reminding system of cervical cancer screening will support them to improve screening attendance. In addition, health-care providers stressed the necessity for educational and awareness campaigns of cervical cancer screening among Libyan women

How Different Are Young Adults From Older Adults When It Comes to Information Privacy Attitudes & Policies?

Media reports teem with stories of young people posting salacious photos online, writing about alcohol-fueled misdeeds on social networking sites, and publicizing other ill-considered escapades that may haunt them in the future. These anecdotes are interpreted as representing a generation-wide shift in attitude toward information privacy. Many commentators therefore claim that young people “are less concerned with maintaining privacy than older people are.” Surprisingly, though, few empirical investigations have explored the privacy attitudes of young adults. This report is among the first quantitative studies evaluating young adults’ attitudes. It demonstrates that the picture is more nuanced than portrayed in the popular media. In this telephonic (wireline and wireless) survey of internet using Americans (N=1000), we found that large percentages of young adults (those 18-24 years) are in harmony with older Americans regarding concerns about online privacy, norms, and policy suggestions. In several cases, there are no statistically significant differences between young adults and older age categories on these topics. Where there were differences, over half of the young adult-respondents did answer in the direction of older adults. There clearly is social significance in that large numbers of young adults agree with older Americans on issues of information privacy. A gap in privacy knowledge provides one explanation for the apparent license with which the young behave online. 42 percent of young Americans answered all of our five online privacy questions incorrectly. 88 percent answered only two or fewer correctly. The problem is even more pronounced when presented with offline privacy issues – post hoc analysis showed that young Americans were more likely to answer no questions correctly than any other age group. We conclude then that that young-adult Americans have an aspiration for increased privacy even while they participate in an online reality that is optimized to increase their revelation of personal data

Phased Tilings and Generalized Fibonacci Identities

Fibonacci numbers arise in the solution of many combinatorial problems. They count the number of binary sequences with no consecutive zeros, the number of sequences of 1\u27s and 2\u27s which sum to a given number, and the number of independent sets of a path graph. Similar interpretations exist for Lucas numbers. Using these interpretations, it is possible to provide combinatorial proofs that shed light on many interesting Fibonacci and Lucas identities (see [1], [3]). In this paper we extend the combinatorial approach to understand relationships among generalized Fibonacci numbers. Given G0 and G1 a generalized Fibonacci sequence G0, G1, G2,... is defined recursively by Gn = Gn-1 + Gn-2 for n ≥ 2. Two important special cases are the classical Fibonacci sequence Fn (F0 = 0 and F1 = 1) and the Lucas sequence Ln (L0 = 2 and L1 = 1). These sequences satisfy numerous relationships. Many are documented in Vajda [6], where, they are proved by algebraic means. Our goal is to recount these identities by combinatorial means. We introduce several combinatorial techniques which allow us to provide new proofs of nearly all the identities in [6] involving generalized Fibonacci numbers. We show that in the framework of phased tilings, these identities follow naturally as the tilings are counted, represented, and transformed in clever ways. These techniques are developed in the next several sections. In the final section, we discuss possible extensions

Multiple Imputation with Diagnostics (mi) in R: Opening Windows into the Black Box

Our mi package in R has several features that allow the user to get inside the imputation process and evaluate the reasonableness of the resulting models and imputations. These features include: choice of predictors, models, and transformations for chained imputation models; standard and binned residual plots for checking the fit of the conditional distributions used for imputation; and plots for comparing the distributions of observed and imputed data. In addition, we use Bayesian models and weakly informative prior distributions to construct more stable estimates of imputation models. Our goal is to have a demonstration package that (a) avoids many of the practical problems that arise with existing multivariate imputation programs, and (b) demonstrates state-of-the-art diagnostics that can be applied more generally and can be incorporated into the software of others