Humane Orientation as a New Cultural Dimension of the GLOBE Project: A Validation Study of the GLOBE Scale and Out-Group Humane Orientation in 25 Countries

We validate, extend, and empirically and theoretically criticize the cultural dimension of humane orientation of the project GLOBE (Global Leadership and Organizational Behavior Effectiveness Research Program). Theoretically, humane orientation is not just a one-dimensionally positive concept about being caring, altruistic, and kind to others as discussed by Kabasakal and Bodur (2004), but there is also a certain ambivalence to this concept. We suggest differentiating humane orientation toward in-group members from humane orientation toward out-group members. A multicountry construct validation study used student samples from 25 countries that were either high or low in humane orientation (N = 876) and studied their relation to the traditional GLOBE scale and other cultural-level measures (agreeableness, religiosity, authoritarianism, and welfare state score). Findings revealed a strong correlation between humane orientation and agreeableness, welfare state score, and religiosity. Out-group humane orientation proved to be the more relevant subfacet of the original humane orientation construct, suggesting that future research on humane orientation should make use of this measure instead of the vague original scale. The ambivalent character of out-group humane orientation is displayed in its positive correlation to high authoritarianism. Patriotism was used as a control variable for noncritical acceptance of one’s society but did not change the correlations. Our findings are discussed as an example of how rigid expectations and a lack of tolerance for diversity may help explain the ambivalent nature of humane orientation

Search for long-lived stopped R-hadrons decaying out-of-time with pp collisions using the ATLAS detector

An updated search is performed for gluino, top squark, or bottom squark R-hadrons that have come to rest within the ATLAS calorimeter, and decay at some later time to hadronic jets and a neutralino, using 5.0 and 22.9 fb(-1) of pp collisions at 7 and 8 TeV, respectively. Candidate decay events are triggered in selected empty bunch crossings of the LHC in order to remove pp collision backgrounds. Selections based on jet shape and muon system activity are applied to discriminate signal events from cosmic ray and beam-halo muon backgrounds. In the absence of an excess of events, improved limits are set on gluino, stop, and sbottom masses for different decays, lifetimes, and neutralino masses. With a neutralino of mass 100 GeV, the analysis excludes gluinos with mass below 832 GeV (with an expected lower limit of 731 GeV), for a gluino lifetime between 10 mu s and 1000 s in the generic R-hadron model with equal branching ratios for decays to q (q) over bar(chi) over tilde (0) and g (chi) over tilde (0). Under the same assumptions for the neutralino mass and squark lifetime, top squarks and bottom squarks in the Regge R-hadron model are excluded with masses below 379 and 344 GeV, respectively.

Improvement of the processes around the radiology workplace : avoidance of time delays

Radiologists have been confronted with multiple new challenges in recent years. While there has been a steady increase in the number of radiological examinations and imaging material per examination, examination protocols have become more complex and highly time-consuming whereas case-based remuneration is on the decline. The identification of inefficient components in examination processes and reporting is therefore essential. Where and why do time delays occur? How can they be avoided? The following article provides a brief overview and is designed to stimulate discussion.

Mobile Temporalities: Place, Ruination and the Dialectics of Time

In this chapter I explore the ambiguous, contradictory and often transient ways the past enters into our lives. I shed light on the interplay of mobility and temporality in the lifeworlds of two Somalis who left Mogadishu with the outbreak of the war in the 1990s. Looking into the ways they actively make sense of this crucial ‘memory-place’ (Ricoeur 2004), a place that that has been turned into a landscape of ruins and rubble, alternative understandings of memory and temporality will emerge. Instead of producing a continuum between here and there, and now and then, the stories and photographs discussed in this chapter form dialectical images – images that refuse to be woven into a coherent picture of the past. By emphasising the dialectical ways these two individuals make sense of Mogadishu’s past and presence, I am following Walter Benjamin’s cue to rethink deeply modern analytical categories such as history, memory and temporality by highlighting the brief, fragmented moments of their appearance in everyday life.

Automatic assessment of time-resolved OCT images for selective retina therapy

Purpose In recent years, selective retina laser treatment (SRT), a sub-threshold therapy method, avoids widespread damage to all retinal layers by targeting only a few. While these methods facilitate faster healing, their lack of visual feedback during treatment represents a considerable shortcoming as induced lesions remain invisible with conventional imaging and make clinical use challenging. To overcome this, we present a new strategy to provide location-specific and contact-free automatic feedback of SRT laser applications. Methods We leverage time-resolved optical coherence tomography (OCT) to provide informative feedback to clinicians on outcomes of location-specific treatment. By coupling an OCT system to SRT treatment laser, we visualize structural changes in the retinal layers as they occur via time-resolved depth images. We then propose a novel strategy for automatic assessment of such time-resolved OCT images. To achieve this, we introduce novel image features for this task that when combined with standard machine learning classifiers yield excellent treatment outcome classification capabilities. Results Our approach was evaluated on both ex vivo porcine eyes and human patients in a clinical setting, yielding performances above 95 % accuracy for predicting patient treatment outcomes. In addition, we show that accurate outcomes for human patients can be estimated even when our method is trained using only ex vivo porcine data. Conclusion The proposed technique presents a much needed strategy toward noninvasive, safe, reliable, and repeatable SRT applications. These results are encouraging for the broader use of new treatment options for neovascularization-based retinal pathologies.

A study of the time complexity of an Elitist Genetic Algorithm used for associating optical observations of MEO and GEO Space Debris

Currently several thousands of objects are being tracked in the MEO and GEO regions through optical means. The problem faced in this framework is that of Multiple Target Tracking (MTT). In this context both the correct associations among the observations, and the orbits of the objects have to be determined. The complexity of the MTT problem is defined by its dimension S. Where S stands for the number of ’fences’ used in the problem, each fence consists of a set of observations that all originate from dierent targets. For a dimension of S ˃ the MTT problem becomes NP-hard. As of now no algorithm exists that can solve an NP-hard problem in an optimal manner within a reasonable (polynomial) computation time. However, there are algorithms that can approximate the solution with a realistic computational e ort. To this end an Elitist Genetic Algorithm is implemented to approximately solve the S ˃ MTT problem in an e cient manner. Its complexity is studied and it is found that an approximate solution can be obtained in a polynomial time. With the advent of improved sensors and a heightened interest in the problem of space debris, it is expected that the number of tracked objects will grow by an order of magnitude in the near future. This research aims to provide a method that can treat the correlation and orbit determination problems simultaneously, and is able to e ciently process large data sets with minimal manual intervention.