An Exploration of Women’s Experiences of Sexism in the UK

It is well documented that sexism is a common experience for women with potentially deleterious effects on their wellbeing. The evidence base pertaining to women’s experience of sexism has prioritised hypotheticoIdeductive methods for inquiry, seeking to test existing theories and determine relationships between psychological correlates. It is possible that these studies do not fully encompass the variety of ways in which women can experience sexism, and risk deIcontextualising what is effectively a social phenomenon. In response, this study adopted a qualitative exploration into the social and psychological processes by which women experience sexism. The aim was to provide fresh and inIdepth understandings of the phenomenon, and prioritise the voices of women in the production of theories pertaining to them. The study resulted in a grounded theory model of Establishing and Policing the Gender Order, which captures two interrelated processes: (1) Reinforcing Inferiority, whereby women are “brainwashed” into accepting their lower social standing, and (2) Punishing Transgression, referring to the normIenforcing processes which penalise women who violate the gender order. The theory also included processes related to Coping with Sexism, indicating feminist identity development as key in helping women to withstand and resist sexism. This study counteracts the postI feminist rhetoric by drawing attention to the ways in which women can be restricted by the patriarchal power structures persisting in contemporary society. These findings can assist clinical psychologist in better serving the needs of female clients and inform policyIlevel advocacy to end women’s oppression. Further feminist and intersectional research is needed to ensure a continued dialogue

An orientation experiment using auditory artificial horizon

Presented at the 10th International Conference on Auditory Display (ICAD2004)An orientation experiment was carried out in a spatially immersive virtual environment. The task of subjects was to navigate with 6 degrees of freedom flying method through a predefined route guided by visual cues. Simultaneously they should keep the model oriented in upright position as well as possible. In the experiment we had three different implementations of auditory artificial horizon, and for the reference the subjects accomplish the task also without the auditory support. According to the results the auditory artificial horizon helps subjects to keep the model oriented during the task

Morphometric Analysis and Prioritization of Watersheds for Soil Erosion Management in Upper Gibe Catchment

As morphometric investigation is connected to prioritization of watershed, morphometric analysis has got a significance role in light of soil and water conservation. In this study, an endeavour for the examination of point by point morphometric analyses of sub-basins was accomplished through the measurement of linear and shape parameters by using ArcGIS-9.3 software. Specifically, linear and shape morphometric parameters like stream length, stream order, drainage density, stream frequency, bifurcation ratio, Length of overland flow, basin perimeter, form factor, compactness coefficient, elongation ratio has been considered. The SRTM DEM (30 x 30 m) is processed for the delineation resulting in 61 sub-basins. The morphometric parameters which affect the soil erodibility are considered to organize the sub-basins and relegate positions on the premise of their association with erodibility to get compound parameter (Cp) esteem. Based on the value of Cp the sub-basin with the lowest Cp value was given the highest priority and then categorized the sub-basins into three classes as high, medium and low in terms of priority. Accordingly, high priority zone comprises 11 sub-basins, medium 19 and low 31 sub-basins. The sub-basins which are falling under high priority were a great deal more defenceless to soil disintegration and ought to be given high need for land preservation measures

Association of Sequential Organ Failure Assessment (SOFA) components with mortality

Background Sequential Organ Failure Assessment (SOFA) is a practical method to describe and quantify the presence and severity of organ system dysfunctions and failures. Some proposals suggest that SOFA could be employed as an endpoint in trials. To justify this, all SOFA component scores should reflect organ dysfunctions of comparable severity. We aimed to investigate whether the associations of different SOFA components with in-hospital mortality are comparable. Methods We performed a study based on nationwide register data on adult patients admitted to 26 Finnish intensive care units (ICUs) during 2012-2015. We determined the SOFA score as the maximum score in the first 24 hours after ICU admission. We defined organ failure (OF) as an organ-specific SOFA score of three or higher. We evaluated the association of different SOFA component scores with mortality. Results Our study population comprised 63,756 ICU patients. Overall hospital mortality was 10.7%. In-hospital mortality was 22.5% for patients with respiratory failure, 34.8% for those with coagulation failure, 40.1% for those with hepatic failure, 14.9% for those with cardiovascular failure, 26.9% for those with neurologic failure and 34.6% for the patients with renal failure. Among patients with comparable total SOFA scores, the risk of death was lower in patients with cardiovascular OF compared with patients with other OFs. Conclusions All SOFA components are associated with mortality, but their weights are not comparable. High scores of other organ systems mean a higher risk of death than high cardiovascular scores. The scoring of cardiovascular dysfunction needs to be updated.Peer reviewe

An integrated hardware/software design methodology for signal processing systems

This paper presents a new methodology for design and implementation of signal processing systems on system-on-chip (SoC) platforms. The methodology is centered on the use of lightweight application programming interfaces for applying principles of dataflow design at different layers of abstraction. The development processes integrated in our approach are software implementation, hardware implementation, hardware-software co-design, and optimized application mapping. The proposed methodology facilitates development and integration of signal processing hardware and software modules that involve heterogeneous programming languages and platforms. As a demonstration of the proposed design framework, we present a dataflow-based deep neural network (DNN) implementation for vehicle classification that is streamlined for real-time operation on embedded SoC devices. Using the proposed methodology, we apply and integrate a variety of dataflow graph optimizations that are important for efficient mapping of the DNN system into a resource constrained implementation that involves cooperating multicore CPUs and field-programmable gate array subsystems. Through experiments, we demonstrate the flexibility and effectiveness with which different design transformations can be applied and integrated across multiple scales of the targeted computing system