Strategies to increase the use and approval of gender-fair language

When masculine forms are used to refer to men and women, this causes male-biased cognitive representations and behavioral consequences, as numerous studies have shown. This effect can be avoided or reduced with the help of gender-fair language. In this talk, we will present different approaches that aim at influencing people’s use of and attitudes towards gender-fair language. Firstly, we tested the influence of gender-fair input on people’s own use of gender-fair language. Based on Irmen and Linner’s (2005) adaptation of the scenario mapping and focus approach (Sanford & Garrod, 1998), we found that after reading a text with gender-fair forms women produced more gender-fair forms than women who read gender-neutral texts or texts containing masculine generics. Men were not affected. Secondly, we examined reactions to arguments which followed the Elaboration Likelihood Model (Petty &Cacioppo, 1986). We assumed that strong pros and cons would be more effective than weak arguments or control statements. The results indicated that strong pros could convince some, but not all participants, suggesting a complex interplay of diverse factors in reaction to attempts at persuasion. The influence of people’s initial characteristics will be discussed. Currently, we are investigating how self-generated refutations, in addition to arguments, may influence initial attitudes. Based on the resistance appraisal hypothesis (Tormala, 2008), we assume that individuals are encouraged in their initial attitude if they manage to refute strong counter-arguments. The results of our studies will be discussed regarding their practical implications.

Automatic Labeling of Software Components and their Evolution using Log-Likelihood Ratio of Word Frequencies in Source Code

As more and more open-source software components become available on the internet we need automatic ways to label and compare them. For example, a developer who searches for reusable software must be able to quickly gain an understanding of retrieved components. This understanding cannot be gained at the level of source code due to the semantic gap between source code and the domain model. In this paper we present a lexical approach that uses the log-likelihood ratios of word frequencies to automatically provide labels for software components. We present a prototype implementation of our labeling/comparison algorithm and provide examples of its application. In particular, we apply the approach to detect trends in the evolution of a software system.

Development of an ex vivo protocol to model bone fracture in laying hens resulting from collisions.

Fractures of the keel bone, a bone extending ventrally from the sternum, are a serious health and welfare problem in free range laying hens. Recent findings suggest that a major cause of keel damage within extensive systems is collisions with internal housing structures, though investigative efforts have been hindered by difficulties in examining mechanisms and likely influencing factors at the moment of fracture. The objectives of this study were to develop an ex vivo impact protocol to model bone fracture in hens caused by collision, to assess impact and bird-related factors influencing fracture occurrence and severity, and to identify correlations of mechanical and structural properties between different skeletal sites. We induced keel bone fractures in euthanized hens using a drop-weight impact tester able to generate a range of impact energies, producing fractures that replicate those commonly found in commercial settings. The results demonstrated that impact energies of a similar order to those expected in normal housing were able to produce fractures, and that greater collision energies resulted in an increased likelihood of fractures and of greater severity. Relationships were also seen with keel's lateral surface bone mineral density, and the peak reactive force (strength) at the base of the manubrial spine. Correlations were also identified between the keel and long bones with respect to both strength and bone mineral density. This is the first study able to relate impact and bone characteristics with keel bone fracture at the moment of collision. Greater understanding of these relationships will provide means to reduce levels of breakage and severity in commercial systems.

Silence That Can Be Dangerous: A Vignette Study to Assess Healthcare Professionals' Likelihood of Speaking up about Safety Concerns

PURPOSE To investigate the likelihood of speaking up about patient safety in oncology and to clarify the effect of clinical and situational context factors on the likelihood of voicing concerns. PATIENTS AND METHODS 1013 nurses and doctors in oncology rated four clinical vignettes describing coworkers' errors and rule violations in a self-administered factorial survey (65% response rate). Multiple regression analysis was used to model the likelihood of speaking up as outcome of vignette attributes, responder's evaluations of the situation and personal characteristics. RESULTS Respondents reported a high likelihood of speaking up about patient safety but the variation between and within types of errors and rule violations was substantial. Staff without managerial function provided significantly higher levels of decision difficulty and discomfort to speak up. Based on the information presented in the vignettes, 74%-96% would speak up towards a supervisor failing to check a prescription, 45%-81% would point a coworker to a missed hand disinfection, 82%-94% would speak up towards nurses who violate a safety rule in medication preparation, and 59%-92% would question a doctor violating a safety rule in lumbar puncture. Several vignette attributes predicted the likelihood of speaking up. Perceived potential harm, anticipated discomfort, and decision difficulty were significant predictors of the likelihood of speaking up. CONCLUSIONS Clinicians' willingness to speak up about patient safety is considerably affected by contextual factors. Physicians and nurses without managerial function report substantial discomfort with speaking up. Oncology departments should provide staff with clear guidance and trainings on when and how to voice safety concerns.

Range-based Weighted-likelihood Particle Filter for RSS-based Indoor Tracking

Attractive business cases in various application fields contribute to the sustained long-term interest in indoor localization and tracking by the research community. Location tracking is generally treated as a dynamic state estimation problem, consisting of two steps: (i) location estimation through measurement, and (ii) location prediction. For the estimation step, one of the most efficient and low-cost solutions is Received Signal Strength (RSS)-based ranging. However, various challenges - unrealistic propagation model, non-line of sight (NLOS), and multipath propagation - are yet to be addressed. Particle filters are a popular choice for dealing with the inherent non-linearities in both location measurements and motion dynamics. While such filters have been successfully applied to accurate, time-based ranging measurements, dealing with the more error-prone RSS based ranging is still challenging. In this work, we address the above issues with a novel, weighted likelihood, bootstrap particle filter for tracking via RSS-based ranging. Our filter weights the individual likelihoods from different anchor nodes exponentially, according to the ranging estimation. We also employ an improved propagation model for more accurate RSS-based ranging, which we suggested in recent work. We implemented and tested our algorithm in a passive localization system with IEEE 802.15.4 signals, showing that our proposed solution largely outperforms a traditional bootstrap particle filter.

Reduction of cement leakage by sequential PMMA application in a vertebroplasty model

PURPOSE Leakage is the most common complication of percutaneous cement augmentation of the spine. The viscosity of the polymethylmethacrylate (PMMA) cement is strongly correlated with the likelihood of cement leakage. We hypothesized that cement leakage can be reduced by sequential cement injection in a vertebroplasty model. METHODS A standardized vertebral body substitute model, consisting of aluminum oxide foams coated by acrylic cement with a preformed leakage path, simulating a ventral vein, was developed. Three injection techniques of 6 ml PMMA were assessed: injection in one single step (all-in-one), injection of 1 ml at the first and 5 ml at the second step with 1 min latency in-between (two-step), and sequential injection of 0.5 ml with 1-min latency between the sequences (sequential). Standard PMMA vertebroplasty cement was used; each injection type was tested on ten vertebral body substitute models with two possible leakage paths per model. Leakage was assessed by radiographs using a zonal graduation: intraspongious = no leakage and extracortical = leakage. RESULTS The leakage rate was significantly lower in the "sequential" technique (2/20 leakages) followed by "two-step" (15/20) and "all-in-one" (20/20) techniques (p < 0.001). The RR for a cement leakage was 10.0 times higher in the "all-in-one" compared to the "sequential" group (95 % confidence intervals 2.7-37.2; p < 0.001). CONCLUSIONS The sequential cement injection is a simple approach to minimize the risk for leakage. Taking advantage of the temperature gradient between body and room temperature, it is possible to increase the cement viscosity inside the vertebra while keeping it low in the syringe. Using sequential injection of small cement volumes, further leakage paths are blocked before further injection of the low-viscosity cement.