The validity of classical trajectory and perturbative quantal methods for electron-impact ionization from excited states in H-like ions

To test the validity of classical trajectory and perturbative quantal methods for electron-impact ionization of H-like ions from excited states, we have performed advanced close-coupling calculations of ionization from excited states in H, Li 2+ and B 4+ using the R -matrix with pseudo states and the time-dependent close-coupling methods. Comparisons with our classical trajectory Monte Carlo (CTMC) and distorted-wave (DW) calculations show that the CTMC method is more accurate than the DW method for H, but does not improve with n and grows substantially worse with Z , while the DW method improves with Z and grows worse with n .

The pervasiveness and trajectory of methodological choices: A 20 year review of human resource management research

This paper examines the methodological choices of researchers studying the HR practices–outcome relationship via a content analysis of 281 studies published across the last twenty years. The prevalence and trajectory of change over time are reported for a wide range of methodological choices relevant to internal, external, construct, and statistical conclusion validity. While the results indicate a high incidence of potentially problematic cross-sectional, single informant, and single level designs, they also reveal significant improvements over time across many validity relevant methodological choices. This broad based improvement in the methodological underpinnings of HR research suggests that researchers and practitioners can view the findings reported in the HR literature with increasing confidence. Directions for future research are provided.

Predictors of caregiver burden across the home-based palliative care trajectory in Ontario, Canada

Family caregivers of patients enrolled in home-based palliative care programmes provide unpaid care and assistance with daily activities to terminally ill family members. Caregivers often experience caregiver burden, which is an important predictor of anxiety and depression that can extend into bereavement. We conducted a longitudinal, prospective cohort study to comprehensively assess modifiable and non-modifiable patient and caregiver factors that account for caregiver burden over the palliative care trajectory. Caregivers (n = 327) of patients with malignant neoplasm were recruited from two dedicated home-based palliative care programmes in Southern Ontario, Canada from 1 July 2010 to 31 August 2012. Data were obtained from bi-weekly telephone interviews with caregivers from study admission until death, and from palliative care programme and home-care agency databases. Information collected comprised patient and caregiver demographics, utilisation of privately and publicly financed resources, patient clinical status and caregiver burden. The average age of the caregivers was 59.0 years (SD: 13.2), and almost 70% were female. Caregiver burden increased over time in a non-linear fashion from study admission to patient death. Increased monthly unpaid care-giving time costs, monthly public personal support worker costs, emergency department visits and low patient functional status were associated with higher caregiver burden. Greater use of hospice care was associated with lower burden. Female caregivers tended to report more burden compared to men as death approached, and burden was higher when patients were male. Low patient functional status was the strongest predictor of burden. Understanding the influence of modifiable and non-modifiable factors on the experience of burden over the palliative trajectory is essential for the development and targeting of programmes and policies to support family caregivers and reduce burden. Supporting caregivers can have benefits such as improved caregiver health outcomes, and enhancing their ability to meet care-giving demands, thereby potentially allowing for longer patient care in the home setting.

Abnormal Pedestrian Trajectory analysis based on arbitrary-length clustering

This papers examines the use of trajectory distance measures and clustering techniques to define normal
and abnormal trajectories in the context of pedestrian tracking in public spaces. In order to detect abnormal
trajectories, what is meant by a normal trajectory in a given scene is firstly defined. Then every trajectory
that deviates from this normality is classified as abnormal. By combining Dynamic Time Warping and a
modified K-Means algorithms for arbitrary-length data series, we have developed an algorithm for trajectory
clustering and abnormality detection. The final system performs with an overall accuracy of 83% and 75%
when tested in two different standard datasets.