This paper aims to discover predictors of academics' work-to-family enrichment at Malaysian Research Universities. The underlying theoretical foundations of this study are the work-family enrichment theory by Greenhaus and Powell and the model of primary antecedents, consequences, and moderators of facilitation by Wayne, Grzywacz, Carlson, and Kacmar. The sample includes 295 academics from three Malaysian Research Universities, and data were gathered via online and offline surveys. This study found that all the selected personal factors (i.e. extraversion, core self-evaluation, overall health), and environmental factors (i.e. social support, job autonomy, supportive work-family culture) were significantly related to work-to-family enrichment among the academics. In addition, extraversion and social support were the best predictors of academics' work-to-family enrichment. Conclusion and implications for theory and practice are discussed in the paper.

In human-automation systems, where high situation awareness is associated with better decision-making, understanding accountability may be crucial to preventing automation complacency. In supervisory control automation, there is some evidence that accountability increases human-automation performance; however, with increasingly intelligent automated agents, human-agent work relationships may resemble more interactive control compared to supervisory control. We investigate the effects of social accountability in a simulated joint task environment and hypothesize that people under an accountability condition would cooperate more with an automated agent than people under a non-accountability condition, in a shared cognitive task. Results from our study support this hypothesis. However, for the accountability group, people's performance in terms of units processed was lower, and this group also self-reported lower performance and attentional control, with higher frustration. These findings indicate that accountability may slow the decision-making process through added pressure, with some costs to short term efficiency.

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Dry drilling of aluminum is environmentally friendly machining technique; in the meanwhile it is difficult to carry out due to aluminums gummy behavior and its tendency to adhere to cutting tools which diminishes hole quality. In spite of recent developments in cutting tool technology, HSS tools are still a cost effective choice due to relatively high toughness and feasibility to manufacture complex geometries of HSS drills besides its low price, make this tool a common choice for drilling soft materials such as aluminum. In this study effect of tool wear on thrust force and torque analyzed and hole quality assessed with respect to tool wear along tool life. Dry drilling on aluminum 2024, performed using HSS and HSCo drills at constant feed rate of 0.04 mm/rev and two cutting speeds of 28 and 94 m/min. Results revealed that the abrasive wear on flank face and BUE on chisel edge, margin and cutting lips were dominant mechanisms in all drills. It was found that with propagating the wear land on tool, thrust force and torque increased in both tools.

Accountability is an ill-defined and underexplored concept in job design, particularly in highly proceduralized environments that must operate under both high throughput and high-security expectations. Using x-ray images from the Airport Scanner game, this paper investigates two mechanisms of accountability: an active condition, and a passive condition. Each group was shown a list of prohibited items, but different feedback was provided. The active group was asked to be vigilant for any possible threat, whereas the passive group was instructed to stick to the list. Data from 76 participants were collected. The active group took longer (+16%) to process fewer (-10%) x-ray images compared to the passive group. As a result, the active group accomplished fewer hits (-14%), but also fewer misses (-31%) compared to the other group. While the active group worked slower, they provided higher quality performance. We conclude that accountability mechanisms can reduce errors if applied appropriately.